Unmanned Arial Vehicles (UAVs) have revolutionalized many industrial, commercial, and recreational applications such as aerial photography and videography, security surveillance, agriculture, mapping and surveying etc. as it inherits economic opportunities and multitude of advantages to the consumers. Drone control using dedicated point to point communication through unlicensed spectrum results in limited data rate, unreliable connections, and insecure communication. An Unmanned Arial Vehicle (UAV) driven by Artificial Intelligence (AI) based autonomous navigation integrated with mind controlling through wireless mobile communication network will be a smart solution to overcome the drawbacks in conventional drone control. UAVs will be guided by the Global Positioning System (GPS) to reach the set point, finding the most secured and the energy efficient path optimizing the battery life. An Artificial Neural Network (ANN) model is developed to stability control and obstacle avoidance. Once an obstacle is detected through the sensors and cameras mounted on UAV, the user will see the degree of freedom in the physical space to escape the obstacle and give the relevant control signals to UAV through his mind for taking responsive actions. The user is able to access real time telemetry data via mobile communication system. In instances where autonomous navigation is not possible, obstacles are detected through the sensors and cameras mounted on UAVs and the user will see the degree of freedom in the physical space to escape the obstacles. Then relevant control signals to the UAV are given through Steady-State Visual Evoked Potential (SSVEP)-based Brain Computer Interface (BCI). Mind controlling allows to control the drone in 3D space with the help of a non-invasive Steady State Visual Evoked Potential (SSVEP) based Brain Computer Interface and an individual’s thoughts. After capturing the Electroencephalogram (EEG) signal by employing a sensor integrated headband the relevant command signal will filtered and extracted and transmitted over the mobile communication network to actuate the drone. Therefore, this proposed autonomous and mind-controlled drone can be operated in Beyond Visual Line of Sight (BVLOS) commercial and industrial applications with reliable and secure connectivity.