In the past decade, Unmanned Aerial Vehicles (UAVs) have grabbed the attention of researchers in academia and industry for their potential use in critical emergency applications, such as providing wireless services to ground users and collecting data from areas affected by disasters, due to their advantages in terms of maneuverability and movement flexibility. The UAVs' limited resources, energy budget, and strict mission completion time have posed challenges in adopting UAVs for these applications. Our system model considers a UAV swarm that navigates an area collecting data from ground IoT devices focusing on providing better service for strategic locations and allowing UAVs to join and leave the swarm (e.g., for recharging) in a dynamic way. In this work, we introduce an optimization model with the aim of minimizing the total energy consumption and provide the optimal path planning of UAVs under the constraints of minimum completion time and transmit power. The formulated optimization is NP-hard making it not applicable for real-time decision making. Therefore, we introduce a light-weight meta-reinforcement learning solution that can also cope with sudden changes in the environment through fast convergence. We conduct extensive simulations and compare our approach to three state-of-the-art learning models. Our simulation results prove that our introduced approach is better than the three state-of-the-art algorithms in providing coverage to strategic locations with fast convergence.

Pune has deployed over 1000 IoT devices (including 1500 CCTV cameras, which are quasi IoT devices), connected with the integrated command and control centre (ICCC). The data feeds are regularly relayed from the sensors. Going ahead the many use cases will need to be explored. Pune is working with IISc and IIT Kanpur for use case development, for example, the availability of parking spaces in the city can be easily identified from sensor data; traffic movements in the city can be tracked and appropriate actions relating to reducing congestion can also be taken based on data relayed from the sensors. Pune is the only city in the country to have participated in a global hackathon, wherein the API based technology architecture allows to expose the data in a secure manner globally to create applications over it.