Abstract

Rapid urbanization and technological progress have intensified the need for sustainable and intelligent urban infrastructures. Smart cities, enabled by the Internet of Things (IoT) and adaptive multi-sensor grids, represent a transformative approach to efficient resource management, real-time monitoring, and data-driven decision-making. This study aims to explore how IoT-based adaptive multi-sensor grids can enhance the sustainability, resilience, and intelligence of modern cities while identifying key innovations, current applications, and challenges in implementing these systems effectively. A systematic literature review was conducted using major academic databases such as IEEE Xplore and Scopus, analyzing peer-reviewed research published between 2020 and 2025 with relevant keywords including “smart city,” “IoT,” and “multi-sensory grid” to gather credible and up-to-date insights. The analysis indicates that IoT-enabled adaptive sensor grids act as the core infrastructure of smart cities, continuously monitoring energy use, traffic movement, air quality, and public health. Integration with Artificial Intelligence (AI) enables real-time, adaptive responses that support predictive power management, dynamic traffic control, and efficient waste management. Despite these advancements, challenges persist in the areas of cybersecurity, data privacy, and interoperability. Overall, adaptive multi-sensor grids are vital to realizing the vision of sustainable and human-centered smart cities. Achieving this goal requires the development of open standards, secure data frameworks, and inclusive governance policies to ensure that IoT-driven urban systems are not only intelligent but also safe, resilient, and equitable.

Key words: adaptive systems, IoT, multi-sensory grid, smart city, urban computing.