Design And Development Of Lake Weed Removal Using IoT
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Date
2024
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Volume Title
Publisher
NHCE
Abstract
This project aims to tackle the pressing environmental issue of invasive river weed proliferation by employing an innovative Internet of Things (IoT) solution. Traditional weed removal methods are often laborious and environmentally disruptive. This project proposes an IoT-based system designed to autonomously detect, identify, and remove river weeds, offering a more efficient and sustainable approach. The primary focus of this endeavor involves the creation of a comprehensive IoT framework integrating various sensors, including cameras, environmental sensors, and GPS, installed on specialized floating devices deployed across targeted river sections. These devices continuously collect data to assess water quality, flow patterns, and identify areas affected by invasive weeds. The collected data undergoes intricate processing utilizing machine learning algorithms, enabling accurate differentiation between invasive weed clusters and indigenous flora. Upon identification, the system triggers automated mechanisms for weed removal, utilizing robotic arms, water-based removal tools, or targeted herbicide application, all while minimizing disturbance to the natural ecosystem. The adaptability and scalability of the IoT platform facilitate remote monitoring and control, allowing real-time tracking of weed removal progress. This feature enables authorities to optimize strategies based on historical data analysis, ensuring efficient and effective weed management. The successful implementation of this IoT-driven solution promises to revolutionize river weed removal strategies, promoting eco-friendly practices that preserve biodiversity, enhance water quality, and restore the balance of river ecosystems. Furthermore, the scalable nature of this system suggests its potential for replication and adaptation in diverse river environments, offering a sustainable solution to a global environmental challenge.