India is a developing country where people depend on natural resources like water, air, land, and others. People extract these natural resources by digging borewells. It is observed that many of the borewells are left uncovered due to various reasons. These uncovered bore wells are the main reasons for the death of children and animals, who accidentally fall into it. According to the Indian census, falling inside the borewells has increased abundantly over the past decade. Many researchers tried to solve this problem using IoT devices which is a time-consuming process and provides only post-rescue solutions. This model strongly believes “Prevention is better than cure”. So, it integrates teachable ML with IoT devices to prevent objects from falling into the borewell. Integrating ML with IoT will automate the process of bore well and save many lives. The main advantage of using Teachable ML is it has a lot of images related to humans, birds, and animals which helps us to prevent training the model from scratch. In this model, if it recognizes an animal or a human being then it automatically closes the door. The model automatically recognizes the darkness of the environment and closes the door throughout the night. All the existing systems provide solutions with IoT devices, but they need human intervention which is automated in this model. The model also provides security by authenticating the system with automatic recognition of the corresponding higher officials. Even after providing prevention measures by chance, if any object falls into the borewell, the corresponding authority will receive an alert notification and a quick rescue team will reach the borewell location.