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We consume an excessive quantity of water in our daily lives, thus it's critical to protect it. It is difficult since there are many causes of pollution, the most of them are caused by humans. Undisposed industrial waste, non-biodegradable pollutants, and over-exploitation of natural resources are some of the primary causes of water pollution issues. This project assists the public in keeping an eye on the quality of the water in lakes, rivers, dams, and reservoirs. People are becoming more concerned as the issue of water contamination poses a serious threat to the sources of our drinking water. The fact that the reservoirs and pipelines that deliver water to homes are often discovered to be in poor condition adds to people's worry about the quality of their drinking water. Controlling water pollution starts with being able to measure its actual amount. We can calculate the water's pH and turbidity values, measure the pollution in the water, and determine the state of the water quality. Following that, we will be in a position to take specific action according to the water quality. [ABSTRACT FROM AUTHOR]

In the field of agriculture, there exists a conflict between animal and human, leading the human life in danger by losing a massive quantity of resources in the forest zone too. To address this issue, smart detection and repulsive system for animal intrusion is done using Deep Neural Network (DNN). Historically, this problem has been solved through both deadly (such as shooting or trapping) and non-lethal (such as educating the public) approaches (e.g., chemical repellents, electric fences). On the other hand, some of the more common approaches result in pollution that is harmful to humans and ungulates equally, while others are prohibitively expensive to maintain and provide only a minor degree of reliability and efficiency at best. The proposed research combines the use of AI Computer Vision with deep convolutional neural networks (DCNN) to detect and locate animals with the use of species-specific ultrasonic emission (i.e., each species of different types) to repel them. An ultrasonic signal tailored to the kind of animal detected is generated by the Animal Repelling Module and sent back to the camera via the edge-computing device. [ABSTRACT FROM AUTHOR]