| Autor: |
B.H.D.D. Priyanka, Pamula Udayaraju, Chandra Sekhar Koppireddy, Alluri Neethika |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Measurement: Sensors, Vol 27, Iss , Pp 100734- (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2665-9174 |
| DOI: |
10.1016/j.measen.2023.100734 |
| Popis: |
The current technological developments have paved the path for various fields to thrive, explore and enrich their current applications with the help of technology such as Artificial Intelligence (AI), Internet Technology, Wireless Technology, and the Internet Of Things (IoT). This research focused on providing energy-efficient software and IoT applications for sustainability. Sustainability is integrating the environmental, social, and economic resources to thrive healthy and different requirements to fulfill human needs simultaneously. It can also be referred to as the maintenance of the environment, especially the natural resources maintaining social equality and economic stability to create a healthy community for this generation and the next generation. For sustainability, this paper proposed a Region-based clustering and cluster-head election model to improve the Energy efficiency of IoT networks deployed in the Agriculture environment (REAN). The proposed methodology uses the Shortest Routing and Less Cost algorithm (SRLC) and Region Clustering and Cluster Head Selection (RCHS) algorithm to provide energy-efficient software and IoT application. The experimental results are used to verify the performance of IoT-based sustainable applications in a real-time environment. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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