An AI-Driven Framework for Energy-Efficient Environmental Monitoring in Smart Cities Using Edge Intelligence
Researchers have developed an AI-driven framework designed to make environmental monitoring in smart cities more energy-efficient. This system utilizes TinyML-enabled edge devices that dynamically activate sensors based on real-time environmental conditions, sensor location, and remaining battery life. By reducing unnecessary sensing and communication, the framework aims to extend sensor lifespan and maintain high monitoring coverage, as demonstrated in city-scale simulations. AI
IMPACT Enhances the efficiency and sustainability of smart city infrastructure through intelligent resource management.