Low-Energy Distributed Sensor Networks for Real-Time Environmental Awareness

Abstract

 Distributed wireless sensor networks must be able to track changes and different environmental structures in real time. The goal of this study is to try to solve the issues that have come up when building long-lasting, high-performance, and energy-efficient heterogeneous field networks. This paper's approach consists of three components: distributed data-fusing methods, energy-efficient communication channels, and adaptive data gathering. Both the requirements for expansion and regular operation will be satisfied by the lower-level node arrangement and power-optimized administration of the entire structure. For two consecutive months, 120 sensor nodes were deployed in various parts of a city as part of a field experiment. According to the comparative analysis above, the modified system has maintained an average node energy consumption of less than 1.2mAh/day and increased operating life by more than 30%. In high-demand situations during peak hours, the network has a packet-loss rate of less than 2% and a delay of less than 200 ms. Furthermore, the data fusion approach is stable in both normal and abnormal settings and has an accuracy of over 98%. The aforementioned findings offer specific technical evidence for the great performance of the combined adaptive scheduling and strong aggregation strategy, as well as some useful recommendations for developing an intelligent and environmentally friendly sensor network in the future. The aforementioned techniques and outcomes will contribute to the future development of a reliable, high-performing sensor network.