Water is the most important resource, it connects every aspect of our lives. But due to increased population, deforestation, industrialization the water sources are being contaminated, depleting. Today, 1 in 9 people lack access to safe water.
Our proposed solution is a sustainable system which powers itself, monitors the water sources (gathering live data and analysis of the data from livers, lakes, ponds) and alerts officials if any of the parameters are above the standard threshold.
The bot will move through different locations collecting the data. The data is then analyzed to find water quality index. This can prevent contaminated water reaching the consumers and the data gathered can be utilized for further development.
The innovative conceptual design of an amphibious vehicle. The base designed in the shape of a boat in which the rear turbine is used to propel the water and act as a wheel. Front wheels also act as flaps to direct the system in the water.
An obstacle detector system based on an IR sensor where the sensor is rotated in 360 degrees is used to avoid collisions. This mechanism is used to avoid the bot from collisions. The design can be fabricated with ease using additive manufacturing techniques.
The system is an effective IOT based machine learning system which will monitor the quality of drinking water in real time and measures the critical parameters like temperature, pH, turbidity, dissolved oxygen and metals.
It is a self-sufficient system, the required power is generated via solar panels and that is used to charge the battery via mppt (Maximum power point tracking system) circuit.
It is an Autonomous waypoint based vehicle system. The Gps coordinates for the vehicles are predefined which can be modified online.
The water vehicle will move through different locations and data is obtained from the sensors. The measured values from the sensors are processed by the controller along with GPS coordinates. These values are then stored in the server via LoRa module. The LoRa gateway has the ability to handle millions of nodes which allows many of these bots monitoring the water sources.
The Machine learning algorithm will monitor the real-time data received from the water vehicle. If any of the parameters does exceed the threshold, an alert is sent to the officials along with the GPS coordinates. This allows the officials to locate the issue and rectify it. All these values are realised in an android application where the user can view the quality of the water resources, different parameters, water quality index. With our solution, we aim for the safe, reliable supply of water for the betterment of mankind.