Recycling of RTOS Systems using Smart Sensor Module
Nishant Mathew Surathu1, T.J. Nagalakshmi2
1Nishant Mathew Surathu, Student of Saveetha School of Engineering, SIMATS, Chennai. (Tamil Nadu), India.
2T.J. Nagalakshmi, assistant professor in Saveetha School of Engineering, SIMATS, Chennai. (Tamil Nadu), India.
Manuscript received on 23 March 2019 | Revised Manuscript received on 30 March 2019 | Manuscript published on 30 March 2019 | PP: 1275-1281 | Volume-7 Issue-6, March 2019 | Retrieval Number: F2936037619/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper proposes a way to construct a financially cheap environment tracking system using the Raspberry Pi single-board PC. The framework was planned using Python Programming and can be controlled remotely. It takes data about the surrounding area through sensors and logs the environment. Test results exhibited that the framework can precisely gauge temperature, moistness, light level or concentrations of the air contamination. It is ideally a system that is developed to measure environmental factors through its different sensors and produce the output of that environment. Society today has a vast accumulation of various electronic devices and technology has been able to operate at a much more efficient manner as time goes by. For example, considering the role of security in our personal device, until the recent few years it was made able to recognize a user through finger print and run facial matching algorithms to provide a more secluded and private mode of access. Technology is moving towards the age of internet of things where devices are to be connected to the cloud storage servers to perform better. Devices are to be upgraded to smart devices that offer a better and improved role of connectivity and promote security. Simpler units are also being made to operate digitally and offer better connectivity through Wi-Fi and Bluetooth and through the use of machine learning algorithms and neural net techniques, they are made to operate as per the each individual user’s life style.
Keywords: Raspberry Pi, Machine language, Interface, Neural net, Devices, Technology, Connectivity, System, Wi-Fi, Bluetooth, Environment, Module, Sensor, Protocols, Program.
Scope of the Article: Program Understanding and System Maintenance