Welcome to Journal of Network Communications and Emerging Technologies (JNCET)

Volume 13, Issue 3, July (2025)                              

S.No	Title & Authors	Full Text
1	An Iterative Systematic Analytical Review of LoRa Optimization Using Machine Learning and IoT Frameworks Neha I. Ingle, Rajeshree D. Raut Abstract - The increasing adoption of LoRa (Long Range) technology in applications of IoT calls for profound knowledge of its optimization strategies to meet the rising efficiency, scalability, and reliability demands across various domains. Most reviews on LoRa optimization, therefore, lack depth and comparative analysis and fail to encompass emerging hybrid methodologies in integrating machine learning, energy-efficient models, and frameworks of IoT. This work addresses these gaps by performing a -based systematic review of state-of-the-art studies, focusing on the performance metrics and optimization strategies used in LoRa implementations in process. The review evaluates methods like ANN, hybrid classifiers, CNN-SVM, energy-efficient clustering algorithms, blockchain integration, and fog/edge computing paradigms. These methods were chosen based on their proven ability to improve the critical metrics such as latency, throughput, energy consumption, and data accuracy levels. ANN and CNN-SVM were highly accurate in predictive analytics. Blockchain ensured data integrity in decentralized systems. Energy-efficient clustering and fog computing were used to overcome scalability and real-time processing issues in vehicular and structural monitoring systems. Through synthesis across diverse applications, this work establishes optimal solutions specially designed for healthcare, agricultural monitoring, environmental sensing, and smart city infrastructures. The results from this investigation show that combining LoRa with ML-based methodologies on top of an IoT framework improves energy efficiency to 56% or even better by minimizing latency and systems reliability of packet delivery higher than 97%. This review not only highlights current best practices but also establishes a foundation for future research in optimizing LoRa technology, which ultimately accelerates its adoption in sustainable IoT solutions.	Download