STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Microcontroller Engineering and Applications Original Research

Innovative Water Distribution Systems: Raspberry Pi Based Adaptive Water Vending Solutions

  1. Diya Gohil Department of Electronics & Communication, Dharmsinh Desai University, Nadiad
  2. Pinkesh Patel Department of Electronics & Communication, Dharmsinh Desai University, Nadiad
  3. Mitesh Limachia Department of Electronics & Communication, Dharmsinh Desai University, Nadiad
  4. Purvang Dalal Department of Electronics & Communication, Dharmsinh Desai University, Nadiad

Abstract

Technology has advanced to the point that many complex equipment and gadgets are now indispensable tools for humankind. Among these, automated vending machines have become a mainstay, simplified a variety of tasks and greatly increased productivity while reduced the need for human involvement. These devices, which have numerous inputs and outputs, can dispense snacks, cold beverages, coffee, tea, water, and more to meet the needs of a diverse clientele. The government of India's "Rail Neer" project features specialized vending machines known as "Water Vending Machines," which are widely present in railway stations, especially in India. These devices give clean and hygienic fluid, which improves public health and convenience for tourists. Within train grounds, the water vending machine effectively supplies inexpensive, clean drinking water. Its design is limited, though, in that each transaction results in the dispensing of a predetermined volume of water. When consumers insert water bottles that are partially filled or of different sizes, this causes problems. As a result, extra water that the vending machine dispenses in these circumstances can be wasted. To properly handle this problem, this study offers an adaptive algorithm that is built into the machine's design. Our goal is to put in place a system that can scan the bottle and collect vital information about its weight and height. With the use of this data, we will be able to determine the ideal time for the machine to dispense water, resulting in effective use and reduced water waste. With Raspberry Pi 3 serving as its processor, the adaptive water vending machine prototype that is shown in this paper has been successfully developed.

Keywords

References (13)

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