Authors :
Dr. Benciya Abdul Jaleel
Volume/Issue :
Volume 10 - 2025, Issue 11 - November
Google Scholar :
https://tinyurl.com/yv6ddbd5
Scribd :
https://tinyurl.com/5n86mfyu
DOI :
https://doi.org/10.38124/ijisrt/25nov843
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Abstract :
The rapid rise in discarded electronic devices, commonly referred to as e-waste, presents serious hurdles for both
environmental policy and municipal waste programmes. In response, this study puts forward BlockTrace, a decentralised
blockchain platform designed to monitor each stage of an electronics product's life, from factory floor to recycling bin. By
creating an immutable digital ledger, the system intends to strengthen transparency, hold manufacturers and consumers
accountable, and streamline recovery operations. Using a quantitative approach, the paper defines specific performance
indicators and describes the data flows needed for deployment, showing how researchers can apply R-based statistical tools
to conduct life-cycle assessments, verify regulatory compliance, and generate predictive forecasts. Although actual adoption
and the collection of real-world data lie outside the current investigation, the proposed model offers a conceptual blueprint
that future field trials can test and refine.
Keywords :
E-Waste Management, Blockchain Technology, Decentralized Systems, Life-Cycle Assessment, Environmental Sustainability, R Programming, Quantitative Analysis, Digital Ledger, Predictive Modeling, Regulatory Compliance.
References :
- Allioui, H., & Mourdi, Y. (2023). Exploring the full potentials of IoT for better financial growth and stability: A comprehensive survey. Sensors, 23(19), 8015.
- Connor-Crabb, A., Bulman, S., Bunyan, C., Guo, Y., Hulme, A., Rainton, S., ... & Toms, S. (2025). Sustainable and Circular Practices in the UK Fashion and Textile Industry.
- De Curtò, J., de Zarzà, I., Fervier, L. S., Sanagustín-Fons, V., & Calafate, C. T. (2025). An Institutional Theory Framework for Leveraging Large Language Models for Policy Analysis and Intervention Design. Future Internet, 17(3), 96.
- Faraj, O. (2024). zero-watermarking for data integrity, secure provenance and intrusion detection in IoT networks (Doctoral dissertation, Institut Polytechnique de Paris; Universitat oberta de Catalunya).
- Hawkins, A. (2022). Enriching, Empowering, and Future-proofing: The benefits of Linked (Open) Data for archives (Doctoral dissertation, University of Liverpool).
- Kumar, K. S., Sulochana, C. H., Jessintha, D., Kumar, T. A., Gheisari, M., & Ananth, C. (2024). Spatio-temporal Data Analytics for e-Waste Management System Using Hybrid Deep Belief Networks. In Spatiotemporal Data Analytics and Modeling: Techniques and Applications (pp. 135-160). Singapore: Springer Nature Singapore.
- Pandya, D. (2024). A Path to Formalization: Exploring the E-Waste Informal Sector's Integration Amid the Transition to Circular Economy (Doctoral dissertation, Université d'Ottawa| University of Ottawa).
- Quinto, S., Law, N., Fletcher, C., Le, J., Antony Jose, S., & Menezes, P. L. (2025). Exploring the E-Waste Crisis: Strategies for Sustainable Recycling and Circular Economy Integration. Recycling, 10(2), 72.
- Shefa, F. R., Sifat, F. H., Uddin, J., Ahmad, Z., Kim, J. M., & Kibria, M. G. (2024, November). Deep Learning and IoT-Based Ankle–Foot Orthosis for Enhanced Gait Optimization. In Healthcare (Vol. 12, No. 22, p. 2273). MDPI.
The rapid rise in discarded electronic devices, commonly referred to as e-waste, presents serious hurdles for both
environmental policy and municipal waste programmes. In response, this study puts forward BlockTrace, a decentralised
blockchain platform designed to monitor each stage of an electronics product's life, from factory floor to recycling bin. By
creating an immutable digital ledger, the system intends to strengthen transparency, hold manufacturers and consumers
accountable, and streamline recovery operations. Using a quantitative approach, the paper defines specific performance
indicators and describes the data flows needed for deployment, showing how researchers can apply R-based statistical tools
to conduct life-cycle assessments, verify regulatory compliance, and generate predictive forecasts. Although actual adoption
and the collection of real-world data lie outside the current investigation, the proposed model offers a conceptual blueprint
that future field trials can test and refine.
Keywords :
E-Waste Management, Blockchain Technology, Decentralized Systems, Life-Cycle Assessment, Environmental Sustainability, R Programming, Quantitative Analysis, Digital Ledger, Predictive Modeling, Regulatory Compliance.