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A Cost-Efficient Environment Monitoring Robotic Vehicle for Smart Industries

Jhonn Pablo Rodr韌uez, David Camilo Corrales, David Griol, Zoraida Callejas, Juan Carlos Corrales

2021Computers, materials & continua/Computers, materials & continua (Print)16 citationsDOIOpen Access PDF

Abstract

Environmental monitoring is essential for accessing and avoiding the undesirable situations in industries along with ensuring the safety of workers. Moreover, inspecting and monitoring of environmental parameters by humans lead to various health concerns, which in turn brings to the requirement of monitoring the environment by robotics. In this paper, we have designed and implemented a cost-efficient robotic vehicle for the computation of various environmental parameters such as temperature, radiation, smoke, and pressure with the help of sensors. Furthermore, the robotic vehicle is designed in such a way that it can be dually controlled by using the remote control along with the distant computer. In addition, contrary to the existing researches, the GSM modules are used to achieve the two-way long distance communication between the robotic vehicle and the distant computer. On the distant computer, the above-mentioned environmental parameters can be monitored along with controlling the robotic vehicle with the help of Graphical User Interface (GUI). In order to fulfill the given tasks, we have proposed two algorithms implemented at the robotic vehicle and the distant computer respectively in this paper. The final results validate the proposed algorithms where the above-mentioned environmental parameters can be monitored along with the smooth-running operation of the robotic vehicle.

Topics & Concepts

RoboticsComputer scienceGSMRobotGraphical user interfaceEnvironmental monitoringReal-time computingInterface (matter)Embedded systemHuman–computer interactionSimulationArtificial intelligenceEngineeringOperating systemMaximum bubble pressure methodBubbleEnvironmental engineeringIoT and Edge/Fog ComputingAir Quality Monitoring and ForecastingDigital Transformation in Industry
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