Integrating Explainable AI in IoT for Enhancing Software Performance
C. Padmaja, T. Kishore Kumar · Advances in computational intelligence and robotics book series · 2025
Explainable AI(XAI) is becoming very important to enhance the transparency and accountability of Internet of Things systems. As IoT networks generate enormous amounts of real-time data, XAI techniques are providing clarity about how AI-driven decisions are being made and breaking the “black box” nature of traditional AI models. XAI allows stake holders from developer to a end user in the following to trust and verify some AI decisions relating to aspects of predictive maintenance, Smart City management and health-care monitoring. Apart from this support given by XAI further strengthens the importance of regulatory compliances. Thus, decisions based on documented AI should not violate law and ethically. It is through the above stated that only one can build accountability while being under its purview. This integration of XAI in IoT will not only ensure responsible decision-making but also build confidence among users for the adoption of IoT solutions.