Sustainable NFTs: Enabling green energy adoption through IoT-integrated Blockchain tokenization of carbon offsets
Naik M., Singh A.P., Pradhan N.R., Mohanty S.N., Rafiq M., Ayouni S., Khan M.I.
Article, International Communications in Heat and Mass Transfer, 2026, DOI Link
View abstract ⏷
The rapid emergence of Non-Fungible Tokens (NFTs) has brought innovation and concerns to the consumer digital world. To promote green energy adoption and to combat environmental impact caused by carbon emission, it is essential to address the growing scrutiny of blockchain-based activities, particularly NFTs, for their energy consumption. Aligning technological advancements with environmental sustainability has therefore become an urgent priority. This paper proposes a blockchain-based Sustainable NFT framework that tokenizes verified carbon offsets using ERC-721 NFTs on the Ethereum blockchain. The framework enables the tokenization of carbon offset credits while linking NFT transactions to verifiable reductions in carbon emissions. This approach ensures that every NFT transaction mitigates its carbon footprint by funding renewable energy projects, reforestation initiatives, or other emission-reduction efforts. By providing a transparent mechanism for measuring environmental impact, Sustainable NFTs actively engage digital creators, collectors, and platforms in combating climate change. Smart contracts enforce carbon offset participation, establishing a consumer NFT marketplace dedicated to sustainable practices and introducing strategies to incentivize user participation in the minting, trading, and retirement of carbon offsets. The significance of this research lies in its potential to transform the NFT ecosystem from an environmental liability into a force for positive change. By encouraging sustainable practices and renewable energy investments within the consumer digital art community, Sustainable NFTs aim to reduce carbon emissions and foster a more responsible digital economy. Finally, the performance of the proposed framework is evaluated using Hyperledger Caliper under varying transaction loads to demonstrate the efficiency and effectiveness of the model.
BFNET: Blockchain Framework for Negawatt Energy Trading and Performance Evaluation
Srinivas O., Singh A.P., Roy D.S., Naik M., Panigrahy S.K., Pradhan N.R.
Conference paper, 2026 IEEE North-East India International Energy Conversion Conference and Exhibition, NE-IECCE 2026, 2026, DOI Link
View abstract ⏷
The negawatt trading approach has emerged with decentralized peer-to-peer energy markets, allowing end users to trade negative or surplus energy directly with each other. However, handling safe and effective transactions presents some difficulties. To address these challenges, the proposed "Blockchain Framework for Negative Energy Trading (BFNET)"network has been designed using Hyperledger Besu as a private blockchain, Ethereum Virtual Machine (EVM) and smart contracts are integrated to provide transparent automated transactions. By employing both off-chain and on-chain permissioning, flexible permission ascription improves control over network users and guarantees trading operations security. The efficiency of the framework is measured using performance indicators such as block import, world state, block network time, and block reward distribution. To understand computational and transaction processing speed, metrics latency, throughput and resources utilization have been examined. Under various circumstances, the result of QBFT's latency was 5x, 4x, and 2x lower than that of Ethash, Clique, and IBFT, respectively. The improved throughput of the QBFT is 1.5x advanced than the IBFT and 3x higher than the Ethash and block import time takes a few to 10s of microseconds, and the block-full import time takes 1-2 seconds. The results performed by Hyperledger Besu greatly improved transaction security and efficiency in Negawatt Chain. By using blockchain, this study offers solutions for both trading and technical issues in the decentralized peer-to-peer negawatt energy market.
A Permissioned Blockchain NFT Framework for Secure Pharmaceutical Asset Ownership and Trading: Permissioned TokenPharma
Article, Boletim da Sociedade Paranaense de Matematica, 2026, DOI Link
View abstract ⏷
Pharmaceutical trading requires a robust system to verify asset authenticity, prevent counterfeiting, and ensure transparent ownership transfer. However, public blockchains face significant challenges, including high latency, unpredictable finality, high transaction gas cost, and the absence of regulatory governance. To address these challenges Hyperledger Besu-enabled Permissioned-TokenPharma (P-TokenPharma) framework was implemented, leveraging the IBFT 2.0 Byzantine Fault Tolerance consensus mechanism. It preserves the fundamental NFT-enabled asset ownership logic and supports peer-to-peer pharmaceutical trading. In addition, it offers regulated node membership, deterministic transaction finality, and governance control enabled by compliance. This system integrates ERC-721 smart contracts, supporting on-chain ownership and metadata stored off-chain via Inter Planetary File System (IPFS). The proposed system significantly improves throughput by 2.1x, reduces transaction latency by up to 45%, and improves efficiency by eliminating gas consumption compared to classical blockchain models. In addition, Ethash consumes 39.23% (1.65x) more memory than Besu-IBFT, and under the same workloads, sustains 1.55x higher CPU overhead than Besu.
A Consumer-Centric Blockchain Framework for Smart and Sustainable EV Charging and Energy Trading Infrastructure
Srinivas O., Pradhan N.R., Singh A.P.
Conference paper, 2026 IEEE North-East India International Energy Conversion Conference and Exhibition, NE-IECCE 2026, 2026, DOI Link
View abstract ⏷
The rapid progress of electric vehicles (EVs) requires smart, sustainable EV-charging infrastructure, energy trading framework deployment, and integration of smart grids. However, existing centralized EV frameworks face challenges such as, transparent energy pricing, single point of failures, limited consumer access, fragmented battery health records, and defective insurance claim procedure. To overcome these issues, we propose a smart and sustainable consumer-centric EV charging infrastructure using Hyperledger Fabric and integrated with smart contracts to ensure secure, immutable decentralized transaction management. Deployed smart contracts automates EV charging appointments, verifies battery swapping, settle payment and insurance claims. Additionally, framework maintains consumer-driven EV charging, energy trading transactions, and interoperable charging stations in decentralized energy ecosystem. These integrations validate the practical deployment of blockchain technology in EV charging stations to enable a smart, sustainable EV charging and energy trading infrastructure for next-generation e-mobility systems.
A Smart and Secure IoT-Enabled Parking System with ML Integration
Samantray B.S., Hemant Kumar Reddy K., Pradhan N.R.
Conference paper, Procedia Computer Science, 2026, DOI Link
View abstract ⏷
In this modern era, a Smart Parking System (SPS) is necessary for maintaining the traffic flow. Smooth traffic flow reduces road congestion and improves the overall parking experience for the public. The existing system faces several challenges, including unproductive space utilization and dependence on manual operations. Manual operations are often vulnerable to human error. To overcome these limitations, this paper proposes a comprehensive IoT-enabled SPS that integrates Hyperledger Fabric (HF), the permissioned blockchain framework. The real-time vehicle detection by ultrasonic sensors, environmental monitoring sensors, and wireless communication for efficient data transmission are integrated into the SPS. The proposed model is implemented by using a sensor and communication module-based hardware simulation. Blockchain technology (BCT) integration ensures the immutability of parking records present inside the distributed ledger. Moreover, BCT also provides integrity and transparency of the data. A miniature implementation of ML is used to predict the basic things, such as parking occupancy and sensor status, which adds flexibility to the system. Additionally, certain performance parameters are evaluated for the SPS, such as success rate, average transaction creation time, and latency. Moreover, a web-based dashboard is constructed for monitoring real-time data like parking availability, blockchain statistics, and sensor status. Simulation results depict the successful integration of IoT and BCT, with an average creation time of 15008 ms, an average success rate of 99.4%, and an average reading latency of 13631 ms. Thus, it ensures the reliability and secure management of parking data. Furthermore, simulations prove that the SPS is performing robustly in differing network conditions.
Fed-ARDP: An Adaptive Reputation-Driven Federated Learning Framework Using Renyi Differential Privacy
Vutukuri Y.K.R., Gudibandla R.S., Goruputi D.S., Kottapalli V., Pradhan N.R., Varri U.S.
Article, IEEE Access, 2026, DOI Link
View abstract ⏷
Federated Learning (FL) approach can promote collaborations of training the predictive model among distributed participants without sharing raw data, to maximize the privacy protection in the heterogeneous networked environment. Conventional FL architectures often suffer from issues like indiscriminate addition of noise in the privacy terms, uneven client participation and unnecessary multiplication of communication rounds there by potentially compromising model fidelity and training through. In response, this study introduces Fed-ARDP, a framework called Adaptive Renyi Differential Privacy in which privacy perturbation is modulated dynamically according to the contributory weight of each client. The methodology quantifies client contributions using a hybrid contribution scoring mechanism combining validation accuracy and cosine similarity between local and global model updates and dynamically adjusts Rényi Differential Privacy (RDP) noise according to the resulting reputation scores. Furthermore, a reputation-weighted aggregation scheme is employed to improve the reliability of global model updates. The proposed framework is evaluated against FedAvg, FedProx, Krum, Bulyan, and Fixed-DP under IID, Non-IID, and adversarial settings to show that Fed-ARDP achieves better model accuracy, has stable convergence, and lower training latency as compared to the baseline federated learning strategies. Therefore, the proposed framework achieves a balanced trade-off between privacy, efficiency, and robustness in multi-party federated learning environments.
BQAREM: Blockchain-Secured Quantum Adaptive Resource Management for Edge Machine Learning
Srinivas O., Krishna M.S.R., Bhavani G.D., Krishna P.G., Srikanth I., Panigrahy S.K., Pradhan N.R.
Conference paper, Procedia Computer Science, 2026, DOI Link
View abstract ⏷
The exponential growth of IoT devices in smart city infrastructures generates vast edge data, demanding secure, low latency, energy-efficient processing. Conventional cloud-centric models face bandwidth bottlenecks, latency overhead, and single-point vulnerabilities, necessitating decentralized management. This research introduces BQAREM: Blockchain-Secured Quantum Adaptive Resource Management for Edge Machine Learning, integrating blockchain security, quantum optimization, reinforcement learning. The framework employs timestamped identity verification, multi parameter trust assessment, and a weighted Proof-of-Stake consensus for secure coordination. Quantum adaptive scheduling and smart contracts ensure efficient, tamper-proof resource allocation, achieving superior latency, energy efficiency, SLA compliance. Comprehensive performance evaluation demonstrates that BQAREM significantly enhances reliability, scalability, intelligent resource orchestration across heterogeneous edge environments. Testing in various smart city scenarios including Smart Grid Control, Traffic Management, Healthcare Monitoring, Surveillance Systems, and Emergency Response demonstrates high accuracy (> 95%), reduced latency (< 50 ms), and efficiency improvements exceeding 80%, with balanced energy use. BQAREM uniquely unifies blockchain-backed trust like timestamped identity + weighted PoS, quantum-adaptive risk-sensitive RL, and multi-resource orchestration with a new Robust Performance Index (RPI) for secure, low-latency, energy-aware Edge-ML scheduling.
Neurovision: A deep learning driven web application for brain tumour detection using weight-aware decision approach
Santhosh T.R.S., Mohanty S.N., Pradhan N.R., Khan T., Derbali M.
Article, Digital Health, 2025, DOI Link
View abstract ⏷
In recent times, appropriate diagnosis of brain tumour is a crucial task in medical system. Therefore, identification of a potential brain tumour is challenging owing to the complex behaviour and structure of the human brain. To address this issue, a deep learning-driven framework consisting of four pre-trained models viz DenseNet169, VGG-19, Xception, and EfficientNetV2B2 is developed to classify potential brain tumours from medical resonance images. At first, the deep learning models are trained and fine-tuned on the training dataset, obtained validation scores of trained models are considered as model-wise weights. Then, trained models are subsequently evaluated on the test dataset to generate model-specific predictions. In the weight-aware decision module, the class-bucket of a probable output class is updated with the weights of deep models when their predictions match the class. Finally, the bucket with the highest aggregated value is selected as the final output class for the input image. A novel weight-aware decision mechanism is a key feature of this framework, which effectively deals tie situations in multi-class classification compared to conventional majority-based techniques. The developed framework has obtained promising results of 98.7%, 97.52%, and 94.94% accuracy on three different datasets. The entire framework is seamlessly integrated into an end-to-end web-application for user convenience. The source code, dataset and other particulars are publicly released at https://github.com/SaiSanthosh1508/Brain-Tumour-Image-classification-app [Rishik Sai Santhosh, “Brain Tumour Image Classification Application,” https://github.com/SaiSanthosh1508/Brain-Tumour-Image-classification-app] for academic, research and other non-commercial usage.
An Energy Efficient Aware Collaborative Duty Cycling Approach for IoT Enabled Smart Industries
Reddy K.H.K., Rao M.G., Pradhan N.R., Sinha Roy D.
Article, IEEE Transactions on Industrial Informatics, 2025, DOI Link
View abstract ⏷
The necessity to address the growing pace of industrialization and resource constraints has underscored the importance of developing innovative Information and Communication Technology solutions. The prevailing “smart industry” paradigm is distinguished by its widespread cyber infrastructure for monitoring and controlling critical industrial assets. In case sudden failure of any equipment shot down the industry and apart from financial loss, it take ample amount of time to recover. To effectively manage the multitude of continuous services while maintaining their quality of service requirements, it is crucial to concurrently utilize sensor-based real-time assessment for predicting employed equipment status and lifespan become a challenging. This research explores the feasibility of enhancing the lifespan of sensors at the fog layer by implementing intelligent sleep and wake-up duty cycles. We propose a clustered-based duty-cycling approach that optimizes service continuity with a minimal number of active sensor nodes using a genetic algorithm. The abovementioned framework simulated in iFogSim simulator and obtained results demonstrate the reduced the energy consumption by approximately 16% to 20% over the energy efficient aware and around 38% to 42% over the K-mean clustering approach with 90% duty cycle.
Blockchain Framework for Negawatt Energy Trading With Incentives and Limits: P2PnW-Chain
Srinivas O., Pradhan N.R., Pratap Singh A.
Article, IEEE Transactions on Consumer Electronics, 2025, DOI Link
View abstract ⏷
The growing adoption of smart grid technologies and energy market deregulation has simplified decentralized peer-to-peer (P2P) energy trading. However, the concept of negawatt trading remains underexplored and relatively unclear. This paper presents P2PnW-Chain, a private, permissioned blockchain-based decentralized negawatt trading framework that addresses critical solutions for low-voltage and grid stability issues in traditional systems. It is built on Ethereum 2.0-compatible Hyperledger Besu, Teku, integrated with Smart Contracts, and utilizes Quorum Byzantine Fault Tolerance (QBFT) consensus mechanism. This system automates negawatt trading, curtailment verification, incentive validation, and transparently grants incentives or penalties to the incentive-consumeers/prosumers based on their energy curtailment during peak hours. It allows dual-role participation for both consumers and prosumers, enhancing system flexibility. It supports on-chain and off-chain permissioning to ensure anonymity, efficiency, and confidentiality. The simulated results of the P2PnW-Chain system moderated low voltage incidents by 15-25%, and reduced low voltage deviations by 10-18%. During peak hours, energy savings improved by 12%, and prosumer participation rate increased up to 70%. Extensive performance evaluations demonstrate that the P2PnW-Chain network maintains a stable CPU load of 76%, with memory consumption between 101–175 MB for 100 nodes, exhibiting low latency and high throughput. Notably, QBFT outperforms IBFT and Ethash by achieving 1.5× and 3× higher throughput, respectively, while reducing latency by up to 5×. These findings validate P2PnW-Chain’s scalability and resilience for decentralized negawatt trading in the modern smart grid ecosystems.
Sustainable Energy-Driven P2P Blockchain System for Tracking EV Performance and Maintenance
Conference paper, 1st International Conference on Sustainable Energy Technologies and Computational Intelligence: Towards Sustainable Energy Transition, SETCOM 2025, 2025, DOI Link
View abstract ⏷
Electric vehicles (EVs) are the foundation of sustainable mobility, yet effective maintenance tracking and performance monitoring is still difficult, particularly in decentralized ecosystems. To fill these gaps, this study suggests a Sustainable Energy-Driven Peer-to-Peer (P2P) Blockchain System that combines blockchain technology, IoT-enabled EV systems, and renewable energy sources. The system lowers operating costs and minimizes the greenhouse effect by using sustainable energy sources like wind and solar to power blockchain nodes, EV charging stations, manufacturing, distributors and, service centers. The decentralized P2P blockchain network guaranteed transparent, immutable tracking of EV performance indicators and maintenance logs. The Istanbul Byzantine Fault Tolerance (IBFT) consensus method provides safe, effective, and energy-efficient transaction validation. EVs' IoT sensors continually gather performance data, including mileage and battery health, which is then stored on the blockchain for computationally intelligent predictive maintenance. The Ethereum Smart contracts improve dependability and reduce administrative burdens by automating warranty monitoring, maintenance schedules, insuring renewal and, service provider communications. Furthermore, by offering verified service records, the blockchain makes ownership transfers easier and increases market trust for used EVs. In line with the objectives of smart cities and green technology, this integrated strategy promotes adopting sustainable energy and improves the lifetime, efficiency, and accountability of EVs.
Quantum-Enhanced Blockchain Architecture: Exploring Security and Scalable High Performance
Srinivas O., Mohanty S., Pradhan N.R.
Conference paper, 2025 5th International Conference on Artificial Intelligence and Signal Processing, AISP 2025, 2025, DOI Link
View abstract ⏷
This paper presents a quantum-enhanced blockchain architecture addressing the dual challenges of quantum vulnerability and scalability limitations in conventional distributed ledgers. We propose a novel framework integrating three key innovations the NIST-standardized Dilithium lattice-based cryptosystem for post-quantum encryption, quantum-resistant binary data structures (1011011 sequences) for integrity verification, and sharded post-quantum key management. Our experimental results demonstrate significant improvements over classical systems, achieving 2,542 TPS throughput (2.7× increase) and reducing cryptographic latency by 67% using BB84 quantum protocols. The architecture provides comprehensive protection against Shor's and Grover's algorithms while maintaining blockchain's decentralized principles through a hybrid quantum-classical consensus mechanism. Comparative analysis reveals our solution outperforms both RSA (classical) and Kyber (hybrid) in all evaluated metrics, including encryption speed (325 MB/s) and key generation time (112 ms). This work establishes a practical pathway for transitioning blockchain infrastructures to quantum-resistant paradigms without compromising performance.
Decentralizing video copyright protection: a novel blockchain-enabled framework with performance evaluation
Article, Frontiers in Artificial Intelligence, 2025, DOI Link
View abstract ⏷
Introduction: Digital content, including images and videos, is increasingly ruling the online world, and so multimedia services form a part of this modern life. However, the digital resources face significant problems, especially regarding copyright infringement. In such an instance, any modification without authority infringes intellectual property rights. Methods: Based on Inter Planetary File System (IPFS) and blockchain technology, a decentralized and distributed framework has been proposed in this study for dealing with insecurity over digital assets and openness of multimedia resources. In this respect, secure, transparent, and immutable transactions in regard to the transfer and ownership of creative works have been facilitated by the use of such a framework. Results: This paper proposes novel decentralized and Blockchain enabled framework to address the problem of video copyright protection by employing solidity based smart contract in a Ethereum network, that allows the content creators to register their videos. The designed smart contract performs copyright checks and release copyright disputes by generating and comparing perceptual hash’s (Phash) for original video and modified video. Discussion: Phash techniques play a crucial role in multimedia content analysis, particularly in verifying the integrity and similarity of the video data under various transformations. Additionally, the framework generates Inter Planetary File System (IPFS) main values that signifies the ownership of the video content. Then it compars the phash values, IPFS and similarly score in public Blockchain environment i.e. Ethereum. The framework performance was measured by simulating the contracts of the Application Binary Interface (ABI), JSON file in the Hyperledger Caliper environment. This result shows the performance in the form of video registration, the measured latency was 5.02 seconds with a throughput of 409.87 seconds. For video verification the latency was 4.57 seconds with a throughput of 484.23 seconds.
An AI-based approach for dynamic routing in IoT networks
Gountia D., Mishra P., Dash R.K., Pradhan N.R., Mohanty S.N.
Article, Peer-to-Peer Networking and Applications, 2025, DOI Link
View abstract ⏷
Dynamic routing problem is an important research challenge for the robust working of the Internet of Things network as many sensors are equipped with limited energy resources. The work carried out in this paper uses a novel energy model to formulate the routing problem for IoT networks. An AI-based approach using a modified A* algorithm proposes a dynamic routing framework for IoT. The simulated results are compared with the k-Means algorithm and genetic algorithm in terms of energy consumption and the number of dead nodes. This comparison reveals the proposed routing framework to outperform than k-Means algorithm and GA by extending the lifetime of the IoT network by a factor of thrice and twice, respectively. Further, the proposed routing framework is also compared over different network configurations.
Blockchain Enabled Secure Data Transmission With NB-IoT Deployment in Smart Agriculture Crop Watch
Mohammed C.P., Chopra S.R., Albadri N., Dekeyser S., Jha S., Roy A., Pradhan N.R.
Letter, Internet Technology Letters, 2025, DOI Link
View abstract ⏷
The integration of Narrowband Internet of Things (NB-IoT) and blockchain technology presents a promising solution to address security and efficiency concerns in data transmission within the Internet of Things (IoT). This research focuses on its application in crop Watch, an agricultural monitoring system. The IoT has revolutionized various industries, including agriculture, by facilitating the collection and transmission of extensive data through sensors and devices. However, ensuring secure and efficient data transmission remains a critical challenge. NB-IoT boasts advantages such as improved coverage in challenging areas, massive connectivity with up to 100 000 links, low energy usage through prolonged discontinuous receipt (eDRX), and cost-effectiveness. Despite these benefits, NB-IoT faces security issues, including authentication, anonymity, and fault tolerance. To enhance data security, public key cryptography is proposed to be incorporated into the NB-IoT framework. Blockchain technology, with its decentralized and immutable nature, can potentially address these security concerns and enhance data accountability. By creating a trust-less and transparent infrastructure, blockchain complements NB-IoT's capabilities and provides a robust mechanism for data verification and integrity. This research paper emphasizes the logical integration of NB-IoT, public key cryptography, and blockchain technology, offering a secure and efficient data transmission framework for agricultural applications like crop Watch. Bridging the gap between data connectivity and security holds promise for advancing agricultural monitoring and driving IoT innovations.
Forest 5.0: Internet of Things-Based Transformation of Forests
Ravi Chandra B., Roy A., Vinay P., Kaur N., Jha S., Pradhan N.R.
Article, Internet Technology Letters, 2025, DOI Link
View abstract ⏷
The phrase “Modernization of forests” highlights the long-term integration of modern technologies into forest management, aiming to enhance ecosystem observation, data collection, and analysis for exploration and improvement. Technologies like the Internet of Things (IoT), Wireless Sensor Networks (WSN), Artificial Intelligence (AI), and the IoT of Trees are key enablers of this shift. This research explores various technological interventions that could significantly benefit forest ecology, focusing on smart sensing, tracking, and analysis systems for detecting wildfires, illegal logging, and poaching. Simplified structures for tasks like vegetation analysis and forest fire predictions are proposed for future use without altering existing forest management systems. Additionally, the study addresses techniques to improve tribal livelihoods, promote small-scale forest product marketing, and enhance wildlife monitoring. Key recommendations include establishing reliable wireless communication networks, continuous real-time monitoring systems, and energy harvesting methods for effective digital forest management.
Assessing the Efficacy of Fog-Assisted Blockchain for Green Energy Applications: A Case study of EV Charging Network
Naik M., Singh A.P., Roy D.S., Pradhan N.R., Lenka R.K., Barik R.K.
Conference paper, 2025 5th IEEE International Conference on Applied Electromagnetics, Signal Processing, and Communication, AESPC 2025, 2025, DOI Link
View abstract ⏷
The integration of green energy sources and electric vehicle is crucial for reducing carbon emissions and to reduce green house gases. However, due to increase adoption of electric vehicle and charging stations, the management of EV charging network poses significant challenges, including energy efficiency, security and scalability. This paper presents an efficient and scalable fog-assisted blockchain-enabled EV charging framework and a case study proposed that reduces transaction latency and increase the transaction throughputs. A fog-assisted blockchain framework is designed and implemented to manage EV charging sessions, optimize energy consumption, and ensure secure transactions. The performance of the proposed framework is evaluated using various metrics, including energy efficiency, transaction latency, and security. The results indicate that the fog-assisted blockchain framework can significantly improve the energy efficiency of EV charging networks, reduce transaction latency, and ensure secure transactions. The study demonstrates the potential of fog-assisted blockchain technology in supporting the widespread adoption of green energy sources and electric vehicles.
TBSSMC: a trusted blockchain solution for social media content integrity and performance simulation
Article, Cluster Computing, 2025, DOI Link
View abstract ⏷
Online event management applications often struggle with issues related to data integrity, security, and trust due to centralized control. Decentralized applications are widely adopted in industries like social networks, offering solutions through transparency and user control. Therefore, a decentralized event management framework that uses blockchain is essential to ensure data protection, immutability, and trustless collaboration. To address these challenges, this paper presents TBSSMC, a decentralized social media application framework. This framework leverages a distributed ledger for secure and reliable data storage which maintains integrity. This framework incorporates smart contract capabilities on the Ethereum Virtual Machine, enabling process automation and secure execution. The framework prototype and its associated algorithms were designed and implemented. Finally, the performance of three primary functions createEvent, joinEvent, and displayEvents was benchmarked using Hyperledger Caliper for 5000 transactions with varying transaction rates. The simulation results indicate that createEvent has an average latency of 10.67 s, while joinEvent and displayEvents have an average latency of 10.24 and 9.04 s, respectively. The throughput averages for the createEvent, joinEvent, and displayEvents functions are 234 TPS, 238 TPS, and 252 TPS, respectively. The average CPU usage ranges from 5.13 to 31.69%, and the memory consumption averages between 731 and 790 MB for the above functions. This ensures that the proposed framework is reliable, secure, scalable, and efficient.
A Framework for Blockchain-Enabled Internet of Electric Vehicles Charging Station Sustainability Performance Evaluation
Naik M., Singh A.P., Pradhan N.R., Almuhaideb A.M., Kumar N.
Article, IEEE Internet of Things Journal, 2025, DOI Link
View abstract ⏷
Electric vehicle (EV) charging stations (CSs) are increasingly prevalent due to the growing adoption of renewable energy. Solar CSs' main difficulties are energy efficiency, security, traceability, and sustainability. This article presents a novel blockchain-enabled EV charging framework that addresses these challenges using the Ethereum virtual machine (EVM), the Metamask wallet, and smart contracts (SCs). This article introduces solarcoins, a digital currency for trading solar energy, which reduces human intervention while fostering trust, transparency, and privacy among EV users. The proposed solution ensures secure communication between CS operators and EV users, enhancing both security and traceability. The proposed solution ensures secure communication between CS operators and EV users, enhancing both security and traceability. To quantify the sustainability and efficiency of the proposed system, the framework performances are tested and evaluated by varying numbers and types (Read, Write, and Transfer) of transactions using Hyperledger caliper and Go Ethereum. The overhaul Performance metrics were measured under varied transaction rates and control parameters by varying the number of validator nodes (1 node to 5 nodes), such as transaction latency, throughput, resource utilization, and so on. The performance of three major functions - open, query, and transfer - was recorded and analyzed. The results show that the query transaction is faster than open and transfer and the latency increases linearly with increased transaction rate. At 1000 transaction per second, the open function has a latency of 260.22 s, whereas the query function has a latency of 104.12 s and the transfer function has a latency of 345.73 s. The average memory usage for 1node-clique is 1224.0 MB, while it is 76.8 MB for 5node-clique. Results reveal that with an increase in the number of cliques (Validator CSs), memory utilization decreased linearly. This happens because all framework transactions are distributed across each EV CS network. The SCs deployment and operational costs were measured. Complexity analysis reveals that functions, such as getStation, getUser, getStationState, etc., exhibit constant time complexity O(1), while the registerUser and addStation functions have linear space and time complexity O(n).
Decentralizing ride-sharing: a blockchain-based application with smart contract automation and performance analysis
Article, Multimedia Tools and Applications, 2025, DOI Link
View abstract ⏷
Blockchain technology is transforming ride-sharing services by shifting from centralized control to decentralized applications (DApps), addressing user privacy, security, and cost-effectiveness. This research presents a novel blockchain-enabled ride-sharing DApp using an Ethereum-based permissioned network. The system employs smart contracts written in Solidity within the Truffle Suite environment, with smart contracts to automate secure transactions. Comprehensive testing was per-formed using Chai and Mocha to ensure robustness, and performance evaluation was conducted with Hyperledger Caliper. The DApp enables seamless ride-finding and payment, with payments held in escrow until service completion, ensuring user trust and operational efficiency. Performance analysis reveals significant advantages over traditional services, including lower latency in query operations and promising throughput growth in transfer functions under high transaction volumes. The proposed system enhances decentralization, reducing security risks and intermediary costs while improving efficiency. These findings highlight the potential for blockchain technology to innovate ride-sharing services and urban mobility. This study introduces a secure, transparent, and efficient ride-sharing platform, showcasing blockchain’s ability to transform vehicular services and promising further innovations as the technology evolves.
Smart Assist System Module for Paralysed Patient Using IoT Application
Kanna R.K., Pradhan N.R., Panigrahi B.S., Basa S.S., Mohanty S.
Article, EAI Endorsed Transactions on Internet of Things, 2024, DOI Link
View abstract ⏷
Those who are hearing impaired or hard of hearing face the most difficult challenges as a result of their handicap. To establish a bond or commit to something, people should be able to express their ideas and feelings via open channels of communication. To solve such issues, simple, transportable, and accurate assistive technology will probably be developed. The glove with sensors and an Arduino microcontroller is the major focus. This system was developed specifically to translate sign languages while analyzing gesture locations using smart technologies in custom gloves. The micro-controller identifies certain hand motions using sensors attached to gloves and converts sensor output data into text. Their capacity to converse may be aided by their ability to read the text on the mobile IOT application. Also, it aids in automating the houses of people with paralysis. It has the capacity to assess biological indicators like pulse and temperature as a patient monitoring device. The system will be put into place with the intention of enhancing the quality of life for people with disabilities and providing additional assistance in bridging the communication gap. It has a low price tag and a small design.
Enhancing Agricultural Sustainability with Deep Learning: A Case Study of Cauliflower Disease Classification
Pradhan N.R., Ghosh H., Rahat I.S., Ramesh J.V.N., Yesubabu M.
Article, EAI Endorsed Transactions on Internet of Things, 2024, DOI Link
View abstract ⏷
The pivotal role of sustainable agriculture in ensuring food security and nurturing healthy farming communities is undeniable. Among the numerous challenges encountered in this domain, one key hurdle is the early detection and effective treatment of diseases impacting crops, specifically cauliflower.This research provides an in-depth exploration of the use of advanced DL algorithms to perform efficient identification and classification of cauliflower diseases. The study employed and scrutinized four leading DL models: EfficientNetB3, DenseNet121, VGG19 CNN, and ResNet50, assessing their capabilities based on the accuracy of disease detection.The investigation revealed a standout performer, the EfficientNetB3 model, which demonstrated an exceptional accuracy rate of 98%. The remaining models also displayed commendable performance, with DenseNet121 and VGG19 CNN attaining accuracy rates of 81% and 84%, respectively, while ResNet50 trailed at 78%. The noteworthy performance of the EfficientNetB3 model is indicative of its vast potential to contribute to agricultural sustainability. Its ability to detect and classify cauliflower diseases accurately and promptly allows for early interventions, reducing the risk of extensive crop damage.This study contributes valuable insights to the expanding field of DL applications in agriculture. These findings are expected to guide the development of advanced agricultural monitoring systems and decision-support tools, ultimately fostering a more sustainable and productive agricultural landscape.
Robust and Predictive Deep Neural Networks for Stock Price Forecasting
Binekar E.B., Raghuvanshi A., Maindola P., Bagra M., Pradhan N.R., Khan T.
Conference paper, 2024 3rd International Conference for Innovation in Technology, INOCON 2024, 2024, DOI Link
View abstract ⏷
Forecasting stock prices has become a widely researched domain, and conventional prediction methods primarily rely on statistical and econometric models. Nevertheless, these methods encounter challenges when confronted with dynamic, nonstationary time series data. The advent of the internet alongside the surging prevalence of social media has brought about a significant shift. Online news snippets and user comments now frequently mirror investor sentiments and perspectives on various stocks, encompassing a wealth of crucial insights that can greatly enhance stock price prediction. In this paper, forecasting of stock prices has been implemented using two cutting-edge deep learning models, namely Long Short-Term Memory and Gated Recurrent Unit. Both models have been evaluated on two publicly available datasets, namely the Google stock price dataset and Tesla stock price dataset. Experimental results show that LSTM has achieved accuracies of 87.91% and 85.67%, while GRU has achieved accuracies of 93.62% and 88.78% on the Google dataset and Tesla dataset, respectively. Keeping in view the complexity of the dataset, the obtained results, in turn, pave the way for practical applications within the dynamic realm of real-time stock market prediction.
Loan Status Prediction System with Ensembled Machine Learning Models: Elevating Information Reliability and Accuracy
Narayanan K.B., Challagundla Y., Maruturi D.R., Pradhan N.R.
Conference paper, Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, 2024, DOI Link
View abstract ⏷
We aimed to develop an integrated tool to more reliably and consistently anticipate lending conditions. The dataset for our analysis, which included a number of feature categories, was offered by Elsevier. The dataset had been uploaded to the application and then preprocessed. At this stage, we encountered missing data and found numerous extra columns, which we promptly eliminated. By eliminating pointless or duplicate features, we hoped to increase the model’s ability to draw out important patterns from the data. Furthermore, we handled missing data by transforming discrete variables and imputing with average/most common values. The dataset was subsequently split into training and testing sets using a 70:30 ratio, and 5-fold cross-validation was used to evaluate the data. We examined a number of techniques for machine learning before choosing on Neural Networks, Gradient Boosting, Random Forest, and an innovative algorithm we created termed “RanNeu” (an Embedded ML model fusing Random Forest with Neural Networks). We carefully selected hyperparameters for each machine learning model in order to maximize performance. Using Lasso (L1) regularization, a constant learning rate, and an initial learning rate (eta) of 0.0100, we improved Gradient Boosting. As a result, we increased the number of neurons in hidden layers for neural networks to a maximum of 300, employed ReLu activation, and applied the Adam solver approach while using regularization with an alpha value of 0.0001 for neural networks.
Blockchain-Enabled Decentralized Crowdfunding Framework for Green Energy Projects
Conference paper, Lecture Notes in Electrical Engineering, 2024, DOI Link
View abstract ⏷
Crowdfunding is an innovative method to raise funds for various purposes, like developing innovative projects, charity, and many more. By using this approach, entrepreneurs who have limited funds to invest in their ideas can get more funding for their projects. There are a few crowdfunding platforms, such as Indiegogo and Kickstarter, that allow entrepreneurs to present their ideas to potential investors. In order to protect investors from fraud, these reliable third-party websites serve as an escrow for the money. However, these sites charge a higher fee for providing services. In this work, we replace intermediaries and their associated costs for fundraising between entrepreneurs and investors by using blockchain technology. Smart contracts are deployed on the blockchain to automate all operations of the framework, and it manages all operations based on the agreements and incentive rules as defined in the smart contract code. This enhances security and transparency among all the stakeholders. First, we designed the framework and then implemented it using Remix, and Solidity language is used to design smart contracts. The Ethereum blockchain network is used for storing and running smart contract transactions. For the front-end, we have user reactjs. Finally, the result of all the crowdfunding applications is described. This application would raise investment in renewable energy infrastructure projects and contribute to achieving the target of net zero emissions in the near future.
Double Auction Strategies for Peer-to-Peer Energy Trading in Smart Grids: A Game Theoretic and Blockchain Approach
Conference paper, ICEPE 2024 - 6th International Conference on Energy, Power and Environment: Towards Indigenous Energy Utilization, 2024, DOI Link
View abstract ⏷
The concept of using blockchain technology for peer-to-peer energy trading (P2PET) in smart grids, particularly employing a double auction-based game theoretic method, is a fascinating application of both blockchain and economic principles. This paper deals with a blockchain-enabled framework for P2PET in a smart grid by using a double auction-based game theory approach. The proposed permissioned blockchain network was developed using Hyperledger Fabric, Minifab and designed by configuring the spec.yaml file. Three smart contracts, or Chaincode namely Double Auction Order, CreateP2PEnergy, and Matching, have been written using Golang and deployed into the blockchain network, thereby creating automatic energy trading transactions between energy producers and consumers. The client communication, such as consumer queries, user input, and producer trading concepts, was designed using the Postman API. Additionally, the double auction framework's performance has been measured by Hyperledger Caliper. Analysis shows that when 1000 transactions were initiated in each round by clients using Hyperledger Caliper and REST API services, the Proof of Elapsed Time (PoET) mechanism successfully processed 946 transactions, in contrast to the 627 transactions managed by Proof of Work (PoW). The outcomes from multiple rounds of testing underscore the enhanced performance of this framework. In summary, the combination of blockchain technology, P2P energy trading, smart grids, and game theory offers a promising approach to revolutionizing the energy sector. By decentralizing energy trading, empowering consumers, and leveraging market mechanisms, this approach has the potential to enhance efficiency, promote renewable energy adoption, and foster a more sustainable energy ecosystem.
TokenGreen: A Versatile NFT Framework for Peer-to-Peer Energy Trading and Asset Ownership of Electric Vehicles
Naik M., Singh A.P., Pradhan N.R., Kumar N., Nayak A., Guizani M.
Article, IEEE Internet of Things Journal, 2024, DOI Link
View abstract ⏷
The rapid increase in the adoption of electric vehicles (EVs) and the installation of charging stations (CSs) are key components for bidirectional energy transfer between EVs and CSs. However, the traditional techniques of energy trading have issues of trust, scalability, traceability, provenance, and authenticity among energy prosumers. To address these challenges, particularly information imbalances between energy buyers and sellers, we propose TokenGreen, a novel framework that leverages blockchain and nonfungible tokens (NFTs) to enable participants to have ownership of energy assets through investments in distributed energy generation, distribution, and clean energy infrastructure, leading to trust and transparency management among the participants. The proposed framework uses Ethereum virtual machine (EVM), ERC-721 NFT, interplanetary file system (IPFS), and solidity smart contracts to develop an NFT-based energy marketplace. Various smart contracts, contract events, functions, and algorithms have been designed and integrated into the energy marketplace to facilitate the minting, creation, purchase, and resale of NFT tokens, including energy trading. To assess the performance of the proposal, experiments are performed using tools, such as Geth, Hyperledger Caliper, and the Ethereum SDK. The obtained results indicate that the average maximum latency for CreateToken reached 12.39 s, while BuyToken and ResellToken reached 11.02 s. Additionally, the average minimum latency for CreateToken, BuyToken, and ResellToken reached 10.46, 10.03, and 9.14 s, respectively. On average, memory consumption ranged from 640 to 775 MB, while CPU usage averaged between 30% and 55% for each function. The performance analysis indicates that CreateToken has low throughput, while BuyToken shows higher, and ResellToken exhibits the highest throughput due to fewer write operations. TokenGreen demonstrates superior performance compared to the existing state of the art, considering the mentioned parameters.
A Novel NFT Framework for Pharmaceutical Asset Ownership and Trading: TokenPharma
Article, IEEE Access, 2024, DOI Link
View abstract ⏷
Blockchain Technology and Non-Fungible Tokens (NFTs) have drawn much interest due to their special qualities, and potential in numerous industries, including Pharma. Recently, medical asset management has grown significantly. This study explores how blockchain and a novel designed framework "TokenPharma"NFTs can transform medical asset ownership in healthcare. It examines cryptographic foundations, decentralized structures, and smart contracts. It addresses patient data security, asset management, and transparent transactions. This paper proposes an NFT-based Pharma marketplace using Solidity smart contracts, Ethereum Virtual Machine, and ERC721 tokens to overcome challenges. The proposed structure is tested by using Remix-IDE, Truffle, Metamask, and the Ethereum Sepolia test network. Various smart contracts, algorithms, events, and functions facilitate NFT token minting, purchase, and sale in the pharmaceutical marketplace. Performance tests using Ethereum SDK, Geth, and Hyperledger Caliper assess the proposal's effectiveness. Following the data, the average latency for Resell_Token, Buy_Token, and Create_Token was 4.27 seconds, 4.68 seconds, and 5.04 seconds, consecutively. Further, the average throughput for Create_Token, Buy_Token, and Resell_Token was 223.83TPS, 262.7TPS, and 268.76TPS accordingly. Resell_Token has the highest throughput since it needs fewer write operations, although Buy_Token has a higher throughput than Create_Token, according to the performance analysis. The function measured the average CPU utilization, while the memory usage fluctuated between 645 to 780 MB on average. TokenPharma outperforms the state-of-the-art when the given parameters are taken into consideration.
NFT based Green Energy and Assets Trading Application over Decentralized Marketplace
Conference paper, 5th International Conference on Energy, Power, and Environment: Towards Flexible Green Energy Technologies, ICEPE 2023, 2023, DOI Link
View abstract ⏷
Digital decentralized marketplace is now becoming more popular since 2015 due to invention of NFT technology. NFT is most successfully implemented in digital contents like art and music and is evolving as a new market for the future. NFT and its underlying technology blockchain is now being diversified into various application areas to solve various requirement of human and its society. In the current global scenario green house effect and its solution though alternating energy sources like renewable energy generation is major challenge due to distributed nature of these sources. Moreover, establishment of such infrastructure need much investments. Distributed management using blockchain technology is the only solution to manage energy generation and exchange between prosumer and consumer. However, to achieve net zero emission (NZE) we need much more investment in the clean energy sector and is not possible unless more and more people join and participate in the investment. This study proposes a new solution for secure and intelligent trading of solar charging stations and electric vehicle equipment in a decentralized digital marketplace, utilizing NFT technology. The approach is designed to improve the reliability and transparency of transactions, providing a more secure and efficient system for trading these valuable assets.
An Industry 4.0 implementation of a condition monitoring system and IoT-enabled predictive maintenance scheme for diesel generators
Mohapatra A.G., Mohanty A., Pradhan N.R., Mohanty S.N., Gupta D., Alharbi M., Alkhayyat A., Khanna A.
Article, Alexandria Engineering Journal, 2023, DOI Link
View abstract ⏷
In most business and residential organizations, Diesel Generators (DG) is a viable supplementary power source for ensuring an undisturbed power supply. The DG is a hybrid machine that generates electrical energy using a Diesel Engine (DE) and an Electric Generator (EG). By routinely monitoring crucial machine parameters, alternative power source efficiency can be improved. Furthermore, Condition Monitoring Systems (CMS) based on the Internet of Things (IoT) have supplanted the traditional equipment maintenance method. Predictive maintenance is also an important building block of Industry 4.0, whose entire process and performance can be fully understood by using IoT-enabled Remote Monitoring (RM) schemes. Firstly, this paper introduces a remote monitoring and data acquisition scheme to realize the concept of predictive maintenance. Secondly, this article discusses a strategy for real-time observation of DG parameters as well as a comprehensive analysis of various metrics. Thirdly, this research article includes a monitoring and analysis scheme of crucial factors in a DG, like the speed of an engine, voltage output, the current produced, power factor, coolant required, fuel consumption, and battery health. Different mathematical models are formulated by correlating experimental data and estimating the coefficients. Finally, to create suitable real-time warnings under critical circumstances, a fuzzy logic-based Decision Support System (DSS) and web-based integration elements are presented.
Multi-Objective Fault-Coverage Based Regression Test Selection and Prioritization Using Enhanced ACO_TCSP
Singhal S., Jatana N., Sheoran K., Dhand G., Malik S., Gupta R., Suri B., Niranjanamurthy M., Mohanty S.N., Ranjan Pradhan N.
Article, Mathematics, 2023, DOI Link
View abstract ⏷
Regression testing of the software during its maintenance phase, requires test case prioritization and selection due to the dearth of the allotted time. The resources and the time in this phase are very limited, thus testers tend to use regression testing methods such as test case prioritization and selection. The current study evaluates the effectiveness of testing with two major goals: (1) Least running time and (2) Maximum fault coverage possible. Ant Colony Optimization (ACO) is a well-known soft computing technique that draws its inspiration from nature and has been widely researched, implemented, analyzed, and validated for regression test prioritization and selection. Many versions of ACO approaches have been prolifically applied to find solutions to many non-polynomial time-solvable problems. Hence, an attempt has been made to enhance the performance of the existing ACO_TCSP algorithm without affecting its time complexity. There have been efforts to enhance the exploration space of various paths in each iteration and with elite exploitation, reducing the total number of iterations required to converge to an optimal path. Counterbalancing enhanced exploration with intelligent exploitation implies that the run time is not adversely affected, the same has also been empirically validated. The enhanced algorithm has been compared with the existing ACO algorithm and with the traditional approaches. The approach has also been validated on four benchmark programs to empirically evaluate the proposed Enhanced ACO_TCSP algorithm. The experiment revealed the increased cost-effectiveness and correctness of the algorithm. The same has also been validated using the statistical test (independent t-test). The results obtained by evaluating the proposed approach against other reference techniques using Average Percentage of Faults Detected (APFD) metrics indicate a near-optimal solution. The multiple objectives of the highest fault coverage and least running time were fruitfully attained using the Enhanced ACO_TCSP approach without compromising the complexity of the algorithm.
CURA: Real Time Artificial Intelligence and IoT based Fall Detection Systems for patients suffering from Dementia
Mishra S., Ngangbam B., Raj S., Pradhan N.R.
Article, EAI Endorsed Transactions on Pervasive Health and Technology, 2023, DOI Link
View abstract ⏷
According to the rising concern of the effects on the families due to dementia suffering patients, we aim to provide caretakers a work-life balance in which monitoring can be done with much more ease and efficiency in real time. This device can also be used in old age homes as well as hospitals which reduces the workload of the caretakers and helps them to easily monitor the patients. We aim to contribute for the betterment of the society and provide a virtual assistance for the patients suffering from dementia. The number of elderly people living alone has been increasing all over the world. If dementia has been detected at an early stage, the progress of disease can be slowed. The patients suffering from dementia are prone to falling quite frequently so as to detect that and to alert their caretakers to take necessary actions. In this study, we proposed a system in which we detect the real time state of the elderly people living alone by using the Machine Learning and IoT (Internet of Things) technology. We installed sensors inside a finger strap which is attached to the person. These sensors can detect the motions of the patient and predict their real time state to have a 24 by 7 support to provide assistance to the patients.
Apple Stock Price Prediction Using Regression Techniques
Shivakoti M., Jeeveth K., Pradhan N.R., Yesu Babu M.
Conference paper, Lecture Notes in Networks and Systems, 2023, DOI Link
View abstract ⏷
In the course of working on this project, we conducted a regression analysis on the stock price of apple between the years 1980 and 2021. For this particular study, we relied on the techniques of Linear, Poisson and lasso regressions, from which we derived the accompanying graphs. These graphs are utilised to make projections on the value of Apple shares for the following year. The model will provide either numbers that are approximately accurate or values that are predictions. The dataset can be acquired from Kaggle, and the reference section will include a link to the site where it can be found. We will also be trying various regression approaches, and we will demonstrate that the regression obtained by linear regression is the most effective method for analysing this dataset.
A Blockchain Enabled Medical Tourism Ecosystem
Pradhan N.R., Sharma H.K., Choudhury T., Mor A., Mohanty S.
Conference paper, Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, 2023, DOI Link
View abstract ⏷
Medical tourism is considered as a potential filed for high growth. There are several problems, including the possible ability of patient tourists to monitor critical elements of healthcare quality and professionals. In addition, patient-doctor confidence, process, openness of risks‚ privacy of the medical record and other threats associated with health in specific treatments come from queries. We study the possible benefits of Blockchain technology in this conceptual paper to answer several outstanding medical tourism concerns. We conclude that technology from Blockchain can serve as the basis for future study. Medical tourism. The four primary objectives that may be reached using Blockchain technology, namely to improve tourism experience, to reward sustainable behavior and to provide benefits for local communities, and to reduce worries about privacy, center on Smart Tourism Destinations. The report also discusses the main hurdles to deploy this new technology successfully. This study seeks to better improve existing understanding regarding blockchain technology’s prospective ramifications within the smart tourism field, particular destinations for smart tourism. In this paper, we have provided the strong need of medical tourism and the significance of Blockchain in secured and reliable medical tourism. Medical record sharing on global platform is security concern for doctor and patients. Blockchain Technology can be silver bullet for enhancing medical tourism for Global medical treatment.
A Blockchain and AI Based Vaccination Tracking Framework for Coronavirus (COVID-19) Epidemics
Pradhan N.R., Mahule R., Wamuyu P.K., Rathore P.K., Singh A.P.
Article, IETE Journal of Research, 2023, DOI Link
View abstract ⏷
The Coronavirus disease, i.e. (COVID-19) pandemic outbreaks has inevitably lead to a corresponding movement restrictive measure by the members of both central and state government leadership. The current limitation of healthcare systems cannot predict the COVID-19 outbreaks and vaccination drive. The need of the hour is to use Blockchain Technology for the construction of immutable ledger. In this paper a Blockchain and Artificial Intelligence (AI) enabled COVID-19 vaccine tracking system has been proposed. The proposed system is designed using the Ethereum Virtual Machine (EVM), decentralized storage by Inter Planetary File System (IPFS) and implemented using Truffle and Ganache Tool. The smart contract interaction among the entities is developed with Drizzle and the front-end using ReactJS. The performance of the proposed framework has been presented with Keccack 256 transaction hash, the total number of transactions, gas consumed by each contract. Additionally the performance parameters such as latency, throughput, traffic in, out, CPU, and memory utilization of the blockchain framework are also calculated. The artificial neural network (ANN) has been used to classify the vaccination group. Such an attempt is a worthwhile addition to the state of the art as evident from the results presented herein. The proposed framework provides a way for vaccinated members of the community to be tracked and indexed so as to avail the benefits, for example, less restrictive movements nationally, internationally, or simply in their own respective communities. This paper leverages the advantages of Blockchain Technology to obtain a reliable and accurate way to facilitate the entire tracking process.
Performance Evaluation and Cyberattack Mitigation in a Blockchain-Enabled Peer-to-Peer Energy Trading Framework
Pradhan N.R., Singh A.P., Sudha S.V., Reddy K.H.K., Roy D.S.
Article, Sensors, 2023, DOI Link
View abstract ⏷
With the electric power grid experiencing a rapid shift to the smart grid paradigm over a deregulated energy market, Internet of Things (IoT)-based solutions are gaining prominence, and innovative peer-to-peer (P2P) energy trading at a micro level is being deployed. Such advancement, however, leaves traditional security models vulnerable and paves the path for blockchain, a distributed ledger technology (DLT), with its decentralized, open, and transparency characteristics as a viable alternative. However, due to deregulation in energy trading markets, most of the prototype resilience regarding cybersecurity attack, performance and scalability of transaction broadcasting, and its direct impact on overall performances and attacks are required to be supported, which becomes a performance bottleneck with existing blockchain solutions such as Hyperledger, Ethereum, and so on. In this paper, we design a novel permissioned Corda framework for P2P energy trading peers that not only mitigates a new class of cyberattacks, i.e., delay trading (or discard), but also disseminates the transactions in a optimized propagation time, resulting in a fair transaction distribution. Sharing transactions in a permissioned R3 Corda blockchain framework is handled by the Advanced Message Queuing Protocol (AMQP) and transport layer security (TLS). The unique contribution of this paper lies in the use of an optimized CPU and JVM heap memory scenario analysis with P2P metric in addition to a far more realistic multihosted testbed for the performance analysis. The average latencies measured are 22 ms and 51 ms for sending and receiving messages. We compare the throughput by varying different types of flow such as energy request, request + pay, transfer, multiple notary, sender, receiver, and single notary. In the proposed framework, request is an energy asset that is based on payment state and contract in the P2P energy trading module, so in request flow, only one node with no notary appears on the vault of the node.Energy request + pay flow interaction deals with two nodes, such as producer and consumer, to deal with request and transfer of asset ownership with the help of a notary. Request + repeated pay flow request, on node A and repeatedly transfers a fraction of energy asset state to another node, B, through a notary.
A blockchain based lightweight peer-to-peer energy trading framework for secured high throughput micro-transactions
Pradhan N.R., Singh A.P., Verma S., Kavita, Wozniak M., Shafi J., Ijaz M.F.
Article, Scientific Reports, 2022, DOI Link
View abstract ⏷
With the electric power grid experiencing a rapid shift to the smart grid paradigm over a deregulated energy market, Internet of Things (IoT) based solutions are gaining prominence and innovative Peer To Peer (P2P) energy trading at micro-level are being deployed. Such advancement, however leave traditional security models vulnerable and pave the path for Blockchain, an Distributed Ledger Technology (DLT) with its decentralized, open and transparency characteristics as a viable alternative. However, due to deregulation in energy trading markets, massive volumes of micro transactions are required to be supported, which become a performance bottleneck with existing Blockchain solution such as Hyperledger, Ethereum and so on. In this paper, a lightweight ’Tangle’ based framework, namely IOTA (Third generation DLT) is employed for designing an energy trading market that uses Directed Acyclic Graph (DAG) based solution that not only alleviates the reward overhead for micro-transactions but also provides scalability, quantum-proof, and high throughput of such transactions at low confirmation latency. Furthermore the Masked Authentication Messaging (MAM) protocol is used over the IOTA P2P energy trading framework that allows energy producer and consumer to share the data while maintaining the confidentiality, and facilitates the data accessibility. The Raspberry Pi 3 board along with voltage sensor (INA219) used for the setting up light node and publishing and fetching data from the Tangle. The results of the obtained benchmarking indicate low confirmation latency, high throughput, system with Hyperledger Fabric and Ethereum. Moreover, the effect of transaction rate decreases when the IOTA bundle size increases more than 10. For bundle size 5 and 10 it behaves absolutely better than any other platform. The speedy confirmation time of transactions in IOTA, is most suitable for peer to peer energy trading scenarios. This study serves as a guideline for deploying, end-to-end transaction with IOTA Distributed Ledger Technology (DLT) and improving the performance of Blockchain in the energy sector under various operating conditions.
Addressing Scheme for Three-Dimensional Central Triangular Matrices in Linear Arrays
Pandey S., Pandey A., Pradhan N.R., Singh A.P., Kumar V.
Conference paper, 2022 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2022, 2022, DOI Link
View abstract ⏷
A matrix, in which most of the elements are present with zero values, is known as sparse matrix. Sparse matrices have many types in which lower and upper triangular matrices are often seen in many applications such as result of linear equation systems. Since many elements of the sparse matrices are present with zero values, so mechanisms to accumulate only non-zero values in disk and memory are desired to save space. Central triangular matrices are special kind of sparse matrices which are analyzed in three-dimensional forms in this paper. A mechanism to store their elements that saves space in memory is also proposed using linear arrays.
Copyright Infringement Detection of Multimedia Objects using K-L Transform
Pandey S., Pradhan N.R., Pratap Singh A., Kushwaha D.S.
Conference paper, 4th International Conference on Energy, Power, and Environment, ICEPE 2022, 2022, DOI Link
View abstract ⏷
The copyright infringement is a critical issue for original copyright owners of multimedia objects like videos, photographs and graphic designs which are uploaded on various peer-to-peer image sharing systems and websites. Copyright infringement negatively impacts copyright holders' interest by performing some extent of modifications in the original uploaded content. Various frame modification and image processing techniques like frame compression, frame speed manipulation, grayscale conversion, cropping and rotation are used by the copyright violators for modification of the original multimedia content. This paper proposes a perceptual hashing technique using Karhunen-Loeve Transform (K-L Transform) for detecting the copyright violations of the multimedia content, so the work acknowledgement should be provided to the original copyright holders.
Blockchain-based smart contract for transportation of blood bank system
Book chapter, The Role of IoT and Blockchain: Techniques and Applications, 2022,
View abstract ⏷
Tracking the shipment of blood is difficult, and violation of maintaining critical parameters leads to wastage and spoilage. IoT sensors can be used to monitor temperature, pressure, humidity, exposed to light, broken seal, etc. In our work, we implemented and tested an Ethereum based smart contract in solidity platform. Although several research works have been carried out in the blood bank inventory system, few of them focus on its security, transparency, and traceability. Health record sharing without modification is essential. Blockchain-based blood bank systems can resolve the need for individuals to access, trace, manage, and share their health and blood-related information which is immutable. Blood traceability can increase the availability systems to blood bank system and determines the number of quantities to transport from cities to a rural area. Delay in availability, results in delay in surgery or may lead to death. The blockchain-based system is a confidential environment which acts as a communication hub between donors, doctors, testing labs, and recipients or patients. To address these issues, we have designed a blockchain-based solution for the blood bank system.
A Flexible Permission Ascription (FPA)-Based Blockchain Framework for Peer-to-Peer Energy Trading with Performance Evaluation
Pradhan N.R., Singh A.P., Kumar N., Hassan M.M., Roy D.S.
Article, IEEE Transactions on Industrial Informatics, 2022, DOI Link
View abstract ⏷
With the proliferation of smart grid and deregulation of the energy market, a wide variety of peer-to-peer (P2P) energy trading systems have emerged. Common challenges for designing such systems include prosumers' privacy and security threats. To this end, Blockchain-based solutions have gained a lot of attention, though most existing solutions have either employed permissionless blockchain, which is far from pragmatic for a P2P energy trading system with peers permitted to join or leave the network at their whim; or relatively secure yet inefficient permissioned blockchains. Hence, this article presents a flexible permissioned ascription (FPA) scheme that uses on-chain and off-chain permissioning scheme via Orion and Metamask wallet. It also employs contract permissioning through a JavaScript based chain code deployed over Hyperledger Besu (an Ethereum based permissioned Blockchain network) with istanbul byzantine fault tolerant (IBFT) 2.0 consensus algorithm. Additionally, the proposed framework is emulated for development of a working prototype for a P2P energy trading system. Its performance evaluation has been conducted and monitored with Grafana, Prometheus, Hyperledger Caliper, and Kibana for parameters such as latency, throughput, success rate, CPU time, block time, block behind time, memory usage, garbage collection (GC) time, and performance of the validator nodes. The latency of IBFT 2.0 was found five times lesser than that of Ethereum and two times lesser than HF RAFT and KAFKA under varying conditions. Also, the measured throughput was 1.5 times higher than RAFT and Kafka and three times higher than that of Ethereum. The average block confirmation time measured is 5-6 s. The GC usage measured very less, i.e., 0.5-0.8%, with the proposed framework. It has been observed that the proposed energy-trading framework provides an efficient performance for deploying, transferring, and querying the energy transaction to a P2P energy-trading Blockchain network when compared with other consensus mechanisms.
A Novel Blockchain-Based Healthcare System Design and Performance Benchmarking on a Multi-Hosted Testbed
Pradhan N.R., Singh A.P., Verma S., Kavita, Kaur N., Roy D.S., Shafi J., Wozniak M., Ijaz M.F.
Article, Sensors, 2022, DOI Link
View abstract ⏷
As a result of the proliferation of digital and network technologies in all facets of modern society, including the healthcare systems, the widespread adoption of Electronic Healthcare Records (EHRs) has become the norm. At the same time, Blockchain has been widely accepted as a potent solution for addressing security issues in any untrusted, distributed, decentralized application and has thus seen a slew of works on Blockchain-enabled EHRs. However, most such prototypes ignore the performance aspects of proposed designs. In this paper, a prototype for a Blockchain-based EHR has been presented that employs smart contracts with Hyperledger Fabric 2.0, which also provides a unified performance analysis with Hyperledger Caliper 0.4.2. The additional contribution of this paper lies in the use of a multi-hosted testbed for the performance analysis in addition to far more realistic Gossip-based traffic scenario analysis with Tcpdump tools. Moreover, the prototype is tested for performance with superior transaction ordering schemes such as Kafka and RAFT, unlike other literature that mostly uses SOLO for the purpose, which accounts for superior fault tolerance. All of these additional unique features make the performance evaluation presented herein much more realistic and hence adds hugely to the credibility of the results obtained. The proposed framework within the multi-host instances continues to behave more successfully with high throughput, low latency, and low utilization of resources for opening, querying, and transferring transactions into a healthcare Blockchain network. The results obtained in various rounds of evaluation demonstrate the superiority of the proposed framework.
A novel Confidential Consortium Blockchain framework for peer to peer energy trading
Pradhan N.R., Singh A.P., Panda K.P., Roy D.S.
Article, International Journal of Emerging Electric Power Systems, 2022, DOI Link
View abstract ⏷
The vital dependence of peer to peer (P2P) energy trading frameworks on creative Internet of Things (IoT) has been making it more vulnerable against a wide scope of attacks and performance bottlenecks like low throughput, high latency, high CPU, memory use, etc. This hence compromises the energy exchanging information to store, share, oversee, and access. Blockchain innovation as a feasible solution, works with the rule of untrusted members. To alleviate this threat and performance issues, this paper presents a Blockchain based Confidential Consortium (CoCo) P2P energy trading system that works on the trust issues among the energy exchanging networks and limits performance parameters. It reduces the duplicate validation by creating a trusted network on nodes, where participants identities are known and controlled. A Java-script-based smart contract is sent over the Microsoft CoCo system with Proof of Elapsed Time (PoET) consensus protocol. Also, a functional model is designed for the proposed framework and the performance bench-marking has been done considering about latency, throughput, transaction rate control, success and fail transaction, CPU and memory usage, network traffic. Additionally, it is shown that PoET's performance is superior to proof of work (PoW) for multi-hosting conditions. The measured throughput and latency moving toward database speeds with more flexible, business-specific confidentiality models, network policy management through distributed governance, support for non-deterministic transactions, and reduced energy consumption.
Author Correction: A blockchain based lightweight peer-to-peer energy trading framework for secured high throughput micro-transactions (Scientific Reports, (2022), 12, 1, (14523), 10.1038/s41598-022-18603-z)
Pradhan N.R., Singh A.P., Verma S., Kavita, Wozniak M., Shafi J., Ijaz M.F.
Erratum, Scientific Reports, 2022, DOI Link
Performance Analysis of a Blockchain Based Peer-to-Peer Energy Trading Framework
Conference paper, 2021 IEEE 4th International Conference on Computing, Power and Communication Technologies, GUCON 2021, 2021, DOI Link
View abstract ⏷
Peer to Peer (P2P) energy trading were introduced to store, manage, share, track, and access the permanently stored energy data. In particular traditional energy trading systems provide a centralized approach and connectivity among the different participating trusted users. Recently Blockchain Technology shows a potential solution to address critical challenges such as gapped communications, security in an untrusted decentralized environment, inefficient transactions retrieval (low throughput, high latency, high CPU and memory utilization, etc.), and scattered energy records. In this paper a framework is proposed, to record the energy transactions, a JavaScript-based smart contract is deployed over the Hyperledger Sawtooth Proof of Elapsed Time (PoET). Additionally, the proposed framework is shown as a working prototype, and the performances are evaluated taking transaction per second, read and write latency, read write throughput, the number of successful and failed transactions, CPU utilization, network traffic input, and output. Also, it is shown that PoET's performance is better than PoW for multi-hosting environments. It has been observed that out of 1000 transactions sent for each round by clients through Hyperledger Caliper and REST API services, PoET could able to perform 946 transactions successfully, whereas PoW completed only 627 transactions. The results obtained in various rounds of evaluation affirm the superiority of the framework.
A Novel Patient-Centric Architectural Framework for Blockchain-Enabled Healthcare Applications
Singh A.P., Pradhan N.R., Luhach A.K., Agnihotri S., Jhanjhi N.Z., Verma S., Kavita, Ghosh U., Roy D.S.
Article, IEEE Transactions on Industrial Informatics, 2021, DOI Link
View abstract ⏷
With the proliferation of information and communication technology in every walks of the society, including healthcare services, digitization, and increased sophistication have been gaining pace, digital healthcare alternatives such as electronic healthcare record (EHR) have gained prominence with increased patients' data volume. However, traditional EHR-based systems are plagued by data loss risks, security and immutability consensus over health records, gapped communication among constituted hospitals, and inefficient clinical data retrieval systems, among others. Blockchain has been developed as a decentralized technology that holds the promise to address the aforesaid facilities in EHR-based systems. This article presents a patient-centric design of a decentralized healthcare management system with blockchain-based EHR using javascript-based smart contracts. A working prototype based on hyperledger fabric and composer technology has also been implemented which guarantees the security of the proposed model. Experiments with the hyperledger caliper benchmarking tool provide performance such as latency, throughput, resource utilization, and so on under varied scenarios and control parameters. The results affirm the efficacy of the proposed approach.
Blockchain Based Smart Healthcare System for Chronic -Illness Patient Monitoring
Conference paper, 3rd International Conference on Energy, Power and Environment: Towards Clean Energy Technologies, ICEPE 2020, 2021, DOI Link
View abstract ⏷
Chronic disease exists over a period of time and it is very crucial because it can affect the health of disability people more. Normally people think that they are not suffering or affected by the disease because they do not have symptoms. But it does not necessarily mean a person with no symptom has no chronic disease. This paper presents design and prototype implementation of a blockchain system which remotely monitors patient health records. The patient monitoring system is a big challenge and other security threats arises as the health care data transferred from one to another and authorization to create and read transactions, is a major concern related to data loss. The data loss of the patient protected health information which are generated from the devices should be handled carefully. So in this paper we proposed a solidity based smart contract run over a Ethereum virtual machine to facilitate the secure analysis and storing of transactions from and to the sensors. Using the Ethereum protocol, based on a private blockchain and writing the smart contracts to keep track of the patient health information. We have created an automatic system through which the sensors collects the data, then communicates with the decentralized application via the smart contract. The method inside the smart contract collects data when they are called, also reads and writes transactions of all events on the Ethereum virtual network. This solidity based smart contract system along with injected web3, metamask, and truffle environment would support alert transaction to the patient and medical professionals.
Smart contracts for automated control system in Blockchain based smart cities
Article, Journal of Ambient Intelligence and Smart Environments, 2021, DOI Link
View abstract ⏷
Nowadays, smart applications are increasing day by day to improve the standard of living in smart cities. A modern-day smart city is characterized by the presence of numerous smart Information and Communication Technology (ICT)-enabled services such as automated healthcare, automatic building monitoring, home automation, smart parking, traffic management, data security, among others. Such cities employ multitudes of Internet of Things (IoT) devices to collect and share data between trusted users by means of a centralized intermediary for monitoring and control of the myriad automatic activities. However, a centralized intermediary is plagued by issues such as single point of failure, risk of data loss, man-in-the-middle attack, and so forth. Blockchain-based smart contracts for automated control in smart cities provide a decentralized and secure alternative. In this paper, an Ethereum based system design for decentralized applications in smart cities has been proposed that enables systems to share data without an intermediary between trusted and non-trusted stakeholders using Ethereum based self-executing contracts. Such contracts allow automated multi-step workflows for smart applications. Two use cases, have been considered namely smart healthcare and smart building monitoring, as proof of stake of the proposed Ethereum based contract. The performance of the proposed scheme for these use cases has been presented with Keccack 256 transaction hash, the total number of transactions, gas consumed by each contract. Such an attempt is a worthwhile addition to state of the art as evident from the results presented herein. The modeling simulation and analysis of hashing power shows that for hashing power greater than 55% the probability of double spending attack reaches to 42% maximum. So it is concluded that the probability of double spending increases with the increase of transaction values.
Blockchain-Enabled Traceable, Transparent Transportation System for Blood Bank
Conference paper, Lecture Notes in Electrical Engineering, 2021, DOI Link
View abstract ⏷
Electronic health records (EHR) and patient health records are an Internet-based health application which is sharable to authorized stakeholders such as doctors, specialist, and patients. One of the important record is blood and sharing the blood record in secured manner is a challenging issue. Blockchain-based blood bank system can resolve the need for individuals to access, trace, manage, share their health and blood-related information, which is immutable. The blockchain-based system provides a secured environment which acts as communication hub between donors, doctors, testing laboratories, and recipients or patients. This work proposes the design of a blockchain-based solution for the blood bank system. Information related to the blood is communicated securely to the intended users from the blood bank. Additionally, the traceability feature included in the proposed system monitors detailed information of blood transfer from excess stock to the nearest place. The system model is designed, implemented and validated using solidity language platform.
Blockchain Based Smart and Secure Agricultural Monitoring System
Conference paper, 2021 5th International Conference on Information Systems and Computer Networks, ISCON 2021, 2021, DOI Link
View abstract ⏷
Nowadays, smart applications are increasing day by day to improve the standard of agriculture in villages. A modern day agriculture is characterised by the presence of numerous smart Information and Communication Technology (ICT)-enabled services such as automated agriculture monitoring, data privacy, among others. Such agriculture monitoring employ multitudes of Internet of Things (IoT) devices to collect and share data between trusted users by means of a centralized intermediary for monitoring and control of the myriad automatic activities. However, a centralized intermediary is plagued by issues such as single point of failure, risk of data loss, man-in-the-middle attack and so forth. Blockchain based smart contracts for automated control in smart agriculture provides a decentralized and secure alternative. With the increasing population across the world, the demand for high-quality products which are fresh as well as healthy is increasing significantly and therefore in a very limited time, the farming and food production have to increase yield significantly. In the coming future, we need to produce double of what we are producing now. There is much research done in the field of smart farming but they don't tackle issues such as storing of data on a central server, complete details of the products from beginning to end which could satisfy a customer as well as stakeholders. In this paper, we presented a novel Blockchain based solutions for secure and smart monitoring of agriculture lands.
