ENVIRO TRACK
Abstract: Our primary objective is to combat the escalating environmental issues gripping our planet. We aim to achieve a sustainable and ecologically balanced world by focusing on the development of innovative devices in crucial areas such as air, water, and soil pollution sensing systems. Additionally, our efforts extend to promoting green building solutions that minimize environmental impact. We emphasize efficient data management for environmental monitoring, allowing us to make informed decisions and take proactive measures. Moreover, our focus also extends to disaster monitoring, enabling us to respond swiftly and effectively to environmental emergencies. The problem of environmental degradation and inefficient monitoring are crucial for several reasons, and their significance extends to various stakeholders, including governments, communities, businesses, and the global population. Addressing environmental challenges is important to safeguard the health of our planet and all its inhabitants. It is vital for the well-being of current and future generations, the stability of global economies, and the preservation of the Earth's natural resources and ecosystems.Our proposed solution involves developing a multifunctional sensing device with a diverse array of sensors for comprehensive environmental monitoring. Seamlessly integrating into existing systems, it will efficiently collect, process, and transmit real-time data to stakeholders, empowering informed decision-making and proactive sustainability measures for communities and ecosystems. While we do not have access to specific real-time data, here are some hypothetical supporting results to demonstrate the effectiveness of the proposed solution:
$1. Enhanced Disaster Response: $The system's timely detection of smoke and earthquake vibrations has led to reduced response times, enabling swift alerts to authorities and accurate GPS data transmission for effective disaster management and mitigation.
$2. Accurate Environmental Monitoring: $The comprehensive suite of sensors in Node 1 has consistently provided precise data on weather parameters, water quality, and disaster events, facilitating informed decision-making and proactive interventions for environmental protection and community safety.
$3. Improved Soil Management: $The soil moisture sensor in Node 2 has demonstrated reliable monitoring of soil moisture levels, aiding farmers and agricultural practitioners in implementing effective irrigation strategies and optimizing crop yield.
$4. Effective Forecasting:$ The machine learning model running on the Raspberry Pi has processed the collected environmental data, resulting in accurate weather forecasting thereby contributing to better planning and preparation for potential environmental events.
Video URL: https://drive.google.com/drive/folders/14pVZ38DJ98qLkN3DVhnh0FCMCCeDNmId?usp=drive_link
Repository URL: https://github.com/ADHITYAVARMAN-SS/Enviro_Track
Submission Number: 12
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