Week 1: Introducing My Senior Project: A Dive into Household Water Usage
March 4, 2024
Welcome to the inaugural blog post for my senior project, where I’ll delve into the motivation behind my endeavor, the project’s objectives, and the groundwork I’ve laid thus far.
Background: Growing up in a family passionate about gardening and taking long showers, discussions about our water bill were commonplace. From lengthy showers to hidden leaks, we were often uncertain about our household water usage. Last year, we discovered a hidden leak in our bathroom that had gone unnoticed for some time, highlighting the need for better insights into our water consumption habits. This personal experience prompted me to explore ways to monitor and understand household water usage more effectively.
Global water usage has significantly increased over the past century, reaching over 4 trillion cubic meters in 2022. California is among the top five U.S. states in water consumption, utilizing an astonishing 38 billion gallons of water daily. During the 2012-2016 drought, urban water usage had to be reduced by at least 25%, highlighting the critical need for water conservation. Former Governor Jerry Brown implemented fines of up to $500 for every 748 gallons of wasted water, emphasizing the importance of addressing water wastage. Although current water bills provide overall usage and costs they lack specific details on individual appliance consumption to assist in giving the opportunity for households to take control of their water.
Purpose: Hence, the primary aim of this project is twofold: to contribute to more sustainable water use practices and to address the lack of awareness among individuals regarding their water consumption habits. By developing a system or tool that enables users to monitor and gain insights into their household water consumption, the project seeks to empower individuals to make informed decisions to reduce overall water usage. Ultimately, the initiative aims to promote water conservation and support more efficient water management practices in the face of escalating water scarcity challenges.
Prior Technical Research: For this project, I’ve decided to employ Python along with machine learning techniques—supervised, semi-supervised, and unsupervised, the choice of which is yet to be determined—to analyze data collected from a Badger Recordall M25 Water Meter, as depicted below. This meter continuously logs water usage in gallons as water flows through it, offering valuable insights into household water consumption patterns.
To retrieve readings from the meter to the Raspberry Pi, I utilize three wires: green (data), black (ground), and red (clock/power), as shown below. While the display on the meter shows the accurate number of gallons, it’s not the data transferred. Instead, I’ve devised a method for decoding the clocked data into gallons and have automated it to continuously record data whenever the meter reading increases (i.e., changes).
Furthermore, I’ll be utilizing Raspberry Pi and PyCharm for software implementation and data analysis. My prior experience with Python and machine learning algorithms provides a solid foundation for this project, enabling me to effectively navigate the technical aspects. This week, my goal is to refine my supervised model using a small set of labeled data and to attempt k-means clustering on the same dataset to explore a simple unsupervised method for training this model.
Stay tuned for future updates as I delve deeper into the development process, exploring data collection methods, algorithm implementation, and the integration of the system into my household.
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