HAZARD RECONNAISSANCE RECOVER USING RASPBERRY PI AND MULTIPLE SENSORS
Scholars' Press
Published on 30. April 2026
Book
Paperback/Softback
92 pages
978-620-9-91908-4 (ISBN)
Description
The proposed system can be further enhanced by integrating advanced sensors such as CO¿, CO, CH¿, and LPG gas sensors to detect harmful gases, along with radiation and vibration sensors for identifying environmental instability. Additionally, pH and moisture sensors can be used for underground analysis to assess soil conditions. Autonomous navigation can be achieved using ultrasonic sensors for obstacle avoidance, camera-based path detection, and advanced SLAM algorithms for real-time mapping and localization. The system can also incorporate AI-based hazard classification, where machine learning models analyze environmental data to determine danger levels and predict potential risks using historical data. Live video surveillance can be implemented by integrating a Pi Camera, enabling real-time monitoring and streaming through platforms like Blynk. Furthermore, drone integration can extend the system's capabilities by enabling airborne hazard detection in high-risk or inaccessible areas. Finally, cloud data analytics can be used to store and analyze collected data over time, supporting long-term environmental safety assessment and decision-making.
More details
Language
English
Dimensions
Height: 220 mm
Width: 150 mm
Thickness: 6 mm
Weight
155 gr
ISBN-13
978-620-9-91908-4 (9786209919084)
Schweitzer Classification
Persons
Dr. M. Aravind Kumar obtained B. Tech Degree in ECE, M.Tech Degree in VLSI System Design from JNTUH, and Ph.D. from GITAM University, Visakhapatnam. He has 15 years of teaching experience. He is a Life member of FIE, ISTE, IETE, SCIEI, UACEE, and IAENG. He Published 45 Research Papers in refereed Journals and Conferences.