Projects and Ongoing Research Works and 

Autonomous drones are one of the key technological advances of the modern era and have a high impact on delivering different items and military usage. Thanks to its advanced technology, which has made the system faster and safer in all its uses. In this paper, a fully autonomous drone is built using model predictive control (MPC) and Feedback Linearization controllers. The quadcopter is modelled for its better performance and mobility. The unmanned aerial vehicle (UAV) uses performance control inputs, and the authors also presented preliminary flight experiments in which the UAV was limited to vertical and yaw movements. The performance is tested in a vacuum as well as against the drag force. For a better understanding of the output of the systems, different user-defined trajectories are built to analyze the performance attributes. In order to evaluate the characteristics and capacities of the overall system, the aforementioned systems underwent carefully planned planning, design, and implementation processes. The accompanying visual aids illustrate various scenarios in which a drone successfully monitors and maintains its set reference trajectory.

We have created a system allowing users to remotely control any industrial process using their mobile devices. The user may keep track of the process and record the data to any server; in this project, we have used MySQL and GRAPHANA to show the data for analysis. Users may also use machine learning to create a prediction model and anticipate their Factory's future output.