8 - Smart AI: adapting to sensor data in practical applications

Adaptive artificial intelligence (AI) plays a vital role in advancing the functionality and efficiency of wireless sensor networks (WSNs) by offering dynamic, data-driven solutions. Unlike conventional AI, which depends on fixed ground truth values, adaptive AI continuously evolves by learning from real-time inputs and network feedback. The main focus of this chapter is to emphasize the use of adaptive AI to enhance the reliability, efficiency, and responsiveness of WSNs across various domains. This responsiveness enables it to adjust to changing network environments, resulting in improved energy management, data processing, and overall system performance. One of its core applications is in energy management, where adaptive AI helps minimize power usage by modifying sensor operations based on current data trends. In data fusion and analysis, it combines information from multiple sensors in real time, leading to enhanced data accuracy and reduced redundancy. It also enables timely detection of anomalies, ensuring reliable data interpretation. Adaptive AI improves network optimization by adjusting routing protocols and balancing network loads in response to shifting traffic patterns, environmental conditions, and node mobility. In environmental monitoring, it prioritizes essential data collection, effectively managing variables like air quality, weather, and water levels while minimizing unnecessary data transmission. In healthcare, adaptive AI supports personalized patient monitoring through wearable sensor analysis. Smart city systems benefit from its ability to manage traffic and environmental data in real time, enhancing urban planning and public services. In industrial automation, it aids in predicting equipment failures and optimizing production. Furthermore, it bolsters security systems by detecting threats in real time and supports agriculture by adjusting irrigation and fertilization based on field conditions. It also plays a crucial role in disaster management through early detection and alert systems.