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@article{201096,
        author = {Saranya S and Nethra M A and Dr. K. S . Vishvaksenan},
        title = {Low-Power LPWAN-Based Environmental Monitoring System with Edge Analytics},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {3019-3023},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=201096},
        abstract = {Increasing pollution levels, changing climate conditions, and rapid growth of urban populations all make environmental monitoring more important than ever before. Traditional methods of monitoring the environment are challenged by high energy consumption, limited ability to scale, and dependence on centrally located, cloud-based data storage and processes. To overcome these challenges, we develop a low-power sensor network for environmental monitoring based on Low- Power Wide Area Network (LPWAN) technology and edge analytics.
In our proposed solution, we use multiple distributed sensor nodes that continuously gather data about their environment (e.g., temperature, humidity, air pollution, noise levels). The sensor nodes share their gathered data among themselves using low- power wide area network protocols to enable very long-range (up to 100 miles) communications while consuming minimal amounts of power. We use edge analytics to perform local data processing and analysis at gateway or edge devices, enabling faster data transmission times, lower data transfer volumes, and reduced reliance on cloud- based services.
Using real-time analysis at the “edge” (out in the field) helps to respond to changes within a managed environment more quickly and improves how quickly anomalies can be detected, which results in faster response times. By leveraging low-power wide-area network (LPWAN) communications and edge intelligence, the proposed approach will improve all aspects of the scalability, energy usage, and reliability of the overall monitoring architecture. This type of monitoring will be well suited for smart cities, agricultural monitoring, industrial processes, and remote environmental monitoring. In fact, for large-scale environmental monitoring solutions, this approach will be cost- effective and sustainable.},
        keywords = {},
        month = {May},
        }