“Are we neglecting the importance of water? Probably, the answer is YES. Go through this different and versatile project to find a solution.
Before diving into the Hardware & Software setup, it is important to first understand what the project is intended to do? Way before starting my IoT & Robotics journey I always wanted to solve the problem of overflowing water tanks.
So, after understanding what do Internet of Things & Machine Learning means I thought of making a project which will eliminate this traditional problem to the full extent. But I was startled to see that there were already thousands of projects covering this area. Almost every sensor out there has been used in these projects.
I think all of the projects which were made earlier have the following drawbacks:
- In the real world scenario the water supply chain, from the water source (eg dam, water facility) to water tanks in our home, is a very long one and we have to admit that the problem of water wastage starts from the initial end of the cycle and penetrates through the very last end of that cycle. All of the previous projects only focus on the very last end of the cycle ie the project only deals with the water tanks of our homes.
- The projects were almost passive. By passive I mean that they will monitor the water level and will turn the water motor off when the water reaches a certain level. This whole computation would be done within the microprocessor and the end-user can’t get to know what is happening inside the code at the moment!
- Less interactive projects. If one can provide some motion or life to the immobile projects then it will greatly enhance the chances of implementing the project in real life.
- Very few of the projects use the concept of Machine Learning. Those who use the ML concepts are just using the pre-built easy structured graphs and anomaly detection things which don’t make much more sense!!
So, I wanted to make a project which must be very different from the existing projects. Then I came up with the project Wheels 4 Water, a perfect amalgamation of IoT, Machine Learning & Cloud. Let me point the main highlights of my project, which make my project stand out from others.
- Apart from the basic sensors, I have used many different sensors. Be it a water flow sensor, solenoid valve,or an analog multiplexer IC (CD4051), all these sensors helped me to almost nullify the water wastage through the whole water supply chain. In this manner, I focused on the whole water supply chain.
- At every instance of the project execution, the end-user will be updated and informed about each major workflow. The project will talk with the user. Thus making the project active.
To make this project more interactive, I dumped the old idea of integrating IFTTT or using the CLI. Even I have not used either the blynk application or the normal switches in my project. Instead of all this, I have provided four custom options to control the project which include a dedicated website, NodeMCU based robot, customized cloud dashboard & voice control (I have not used any drag and drop feature of Blynk or IFTTT applications)
- Rather than using simple and pre-built ML systems I used the Iterative Dichotomiser 3algorithm and implemented it via Python so that the robot can make decisions on its own after analyzing the dataset.”