The Internet of Things (IoT) has emerged as one of the most vital technologies of the twenty-first century in recent years. IoT can be described as the common physical objects that are digitally connected. Things in IoT refers to all the physical objects like sensors that can be used to be embedded with software. A drone is a type of unmanned aerial vehicle. It does not have a human pilot on board, as the name implies. Because of its compact size and lightweight mechanism, it has a lot of potential to carry out tasks that will make our lives easier. Drones may be controlled via different mediums like wifi transmissions and radio frequency signals. In the case of radio frequency drones, the drones are typically controlled via a remote controller, although wifi equipped drones may also be controlled by devices with wifi access, such as smart phones. Due to the qualities of the drone, they have become popular for use in both legal and unlawful activities, such as delivering illegal materials across country borders. Anti-drone systems are thus being developed in anticipation of their potential use in future smart cities. However, the cost of each anti-drone technology is currently too exorbitant to be employed in civilian settings. As a result, we've offered a notion for creating an anti-drone system utilizing IoT technologies in this article. Making an anti-drone system with Raspberry Pi and Wifi-Pineapple is the subject of this study. Wireless assaults can knock down or even take control of wifi-enabled drones, forcing them to make a safe or emergency landing. In this paper we have tried to bring down the drone in the vicinity of the system by means of a wireless attack using the above components. The wireless attack consists of deauthentication attack and wireless password cracking. In this study, the findings and the attack success rate have been described. The DJI Tello, a WIFI-enabled drone, was the one used in this experiment, and the system was automated so that it could decide for itself how to carry out the attacks. © 2022 IEEE.