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 Free Download AUTOMATIC SANITARY ROBOT WITH OPTIMIZED PERFORMANCE OF ARBITRARY TRACK SELECTION USING PIC MICROCONTROLLER by KARTHIK SABARI, SABARI PRASATH English | 2017 | ISBN: N/A | ASIN: B01K24JXYC | 51 pages | EPUB | 0.71 Mb The advent and progress of Robotics have comprised in itself the Robot giants to micro bots that rule the roost and have revolutionized the way of living, work and entertain people. The Tech-savvy world of today has umpteen varieties of Robot that do work ranging from rifles to more complicated tasks. The prototype floor cleaning models to Roomba version and later to the latest smart versions like the Robovac boast of cleaning flawlessly but their size and work mechanism are centred around simple, repetitive motions and sophisticated machine logic hidden beneath its coarse exteriors. The prototype models required regular charging on wall plugs while the latest versions have self-charging features and the latest iRobot offers a fast recharging pack. Whatever modifications have been done in the battery potential or work efficiency, the floor cleaning Robots can do only limited tasks like either cleaning or mopping in isolation. A working model that combines in itself both the cleaning and mopping options simultaneously in a single version is still a dream afar. The proposed project specimen addresses that specific lacuna thereby merging a dual action in a simple, user-friendly, affordable, multi-purpose and smart device. The proffered automated sanitary robot is used for multi-purpose floor cleaning and provides a germ-free environment. The overall process is controlled by embedded C program. Once started, the modules will continuously run and when the work is completed, whisper-quiet operation will take place.  Free Download AI-Powered IoT in the Energy Industry: Digital Technology and Sustainable Energy Systems English | 2023 | ISBN: 3031150430 | 556 Pages | EPUB (True) | 44 MB AI-Powered IoT in the Energy Industry: Digital Technology and Sustainable Energy Systems looks at opportunities to employ cutting-edge applications of artificial intelligence (AI), the Internet of Things (IoT), and Machine Learning (ML) in designing and modeling energy and renewable energy systems. The book's main objectives are to demonstrate how big data can help with energy efficiency and demand reduction, increase the usage of renewable energy sources, and assist in transitioning from a centralized system to a distributed, efficient, and embedded energy system. Contributions cover the fundamentals of the renewable energy sector, including solar, wind, biomass, and hydrogen, as well as building services and power generation systems. Chapters also examine renewable energy property prediction methods and discuss AI and IoT prediction models for biomass thermal properties. |
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