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All Journal Aerospace Engineering Journal of Geosciences and Environmental Studies Jurnal Teknokes
Shah, Krishna Bikram
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Aerospace Engineering Astronomy Biochemistry, Genetics & Molecular Biology Computer Science & IT Earth & Planetary Sciences Electrical & Electronics Engineering Energy Engineering Environmental Science Social Sciences

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Water Sustainability Enhancement with UAV and AIoT: An Integrated Technology for Water Quality and Flood Hazard Monitoring using the Internet of Drones Paneru, Biplov; Paneru, Bishwash; Sapkota, Sanjog Chhetri; Shah, Krishna Bikram; Poudel, Yam Krishna
Aerospace Engineering Vol. 1 No. 4 (2024): October
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/aero.v1i4.2773

Abstract

Globally, there are challenges in minimizing the effects of water pollution and global warming everywhere in the world. In order to map the flood conditions, we want to apply a sensor network connected to a Esp32 and Tensorflow lite integrated system for drone-based water surface waste collection. Finally, a GSM sim 800L Module incorporated is used to send notifications to the user about the monitored conditions, such as trash level and other data. An ultrasonic sensor is utilized to detect the water level. The outcome shows that there is a high chance of tracking water levels and monitoring floods. By using this innovative technology, users can receive warnings and be warned remotely. The Inception-v3 model on clean and unclean water images obtained 97% accuracy on testing USING Inception-v3 and using the proposed circuit diagram a prototype is developed for possible deployment in such water resource region for possible operation and application is presented in the paper.
Water Sustainability Enhancement with UAV and AIoT: An Integrated Technology for Water Quality and Flood Hazard Monitoring using the Internet of Drones Paneru, Biplov; Paneru, Bishwash; Sapkota, Sanjog Chhetri; Shah, Krishna Bikram; Poudel, Yam Krishna
Journal of Geosciences and Environmental Studies Vol. 2 No. 1 (2025): March
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/ijgaes.v2i1.3343

Abstract

Globally, there are challenges in minimizing the effects of water pollution and global warming everywhere. We want to apply a sensor network connected to an Esp32 and Tensorflow lite integrated system to map the flood conditions for drone-based water surface waste collection. Finally, a GSM sim 800L Module is incorporated to notify the user about the monitored conditions, such as trash level and other data. An ultrasonic sensor is utilized to detect the water level. The outcome shows a high chance of tracking water levels and monitoring floods. This innovative technology allows users to receive warnings and be warned remotely. The Inception-v3 model on clean and unclean water images obtained 97% accuracy on testing USING Inception-v3, and using the proposed circuit diagram, a prototype is developed for possible deployment in such water resource region for possible operation and application is presented in the paper.
Automated Environmental Stewardship: A Ribbon-Cutting Robot with Machine Vision for Sustainable Operation Paneru, Biplov; Paneru, Bishwash; Poudyal, Ramhari; Shah, Krishna Bikram; Poudyal, Khem Narayan; Poudel, Yam Krishna
Jurnal Teknokes Vol. 17 No. 1 (2024): March
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This paper provides a novel way for automating ribbon-cutting rituals that use a specifically constructed robot with superior computer vision capabilities. The system achieves an outstanding 92% accuracy rate when assessing picture data by using a servo motor for ribbon identification, a motor driver for robot movement control, and nichrome wire for precision cutting. The robot's ability to recognize and interact with the ribbon is greatly improved when it uses a Keras and TensorFlowbased red ribbon identification model which obtained accuracy of about 93% on testing set before deployment in system. Implemented within a Raspberry Pi robot, the method exhibits amazing success in automating ceremonial activities, removing the need for human intervention. This multidisciplinary method assures the precision and speed of ribbon-cutting events, representing a significant step forward in the merging of tradition and technology via the seamless integration of robots and computer vision.
Co-Authors Paneru, Biplov Paneru, Bishwash Poudel, Yam Krishna Poudyal, Khem Narayan Poudyal, Ramhari Sapkota, Sanjog Chhetri