An AI-Driven Framework for Energy-Efficient Environmental Monitoring in Smart Cities Using Edge Intelligence
A new AI-driven framework has been proposed for energy-efficient environmental monitoring in smart cities. This framework utilizes edge intelligence to dynamically activate sensors based on real-time conditions, thereby reducing energy consumption and extending sensor lifespan. The results from city-scale simulations indicate significant improvements over traditional monitoring strategies.
- ▪The framework leverages TinyML-enabled edge devices for efficient monitoring.
- ▪Sensors are activated based on a utility function considering environmental conditions and battery lifespan.
- ▪City-scale simulations show a significant reduction in energy consumption compared to static and periodic sensing strategies.
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Computer Science > Distributed, Parallel, and Cluster Computing arXiv:2605.22824 (cs) [Submitted on 31 Mar 2026] Title:An AI-Driven Framework for Energy-Efficient Environmental Monitoring in Smart Cities Using Edge Intelligence Authors:Yichen Liu, Imam Akintomiwa Akinlade, Xiaochong Jiang, Wenting Yang, Shiqi Yang View a PDF of the paper titled An AI-Driven Framework for Energy-Efficient Environmental Monitoring in Smart Cities Using Edge Intelligence, by Yichen Liu and 4 other authors View PDF HTML (experimental) Abstract:Environmental monitoring is a crucial component of the smart city infrastructure. It enables informed decision making which enhances sustainability, public health and urban planning.
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