An improved automated electronic sensor system with IOT

• Main Author: Ong, Crement Wen Yao
• Format: Final Year Project / Dissertation / Thesis
• Published: 2022
• Subjects: T Technology (General); TH Building construction
• Online Access: http://eprints.utar.edu.my/4829/1/fyp_ES_OCWY_2022.pdf; http://eprints.utar.edu.my/4829/

An existing automated electronic sensor system for surface roughness profiling is improved and renamed “ProSight Surface Profiler”. It is aimed to integrate a newly developed automated surface roughness data analysis programme that connects with the prototype surface profiler. The application is managed able to automate the output of surface roughness parameters, including RMS and autocorrelation length. The software supports real-time data analysis. The software can merge effortlessly with the hardware. The resulting graph is flexible, allowing the user to examine it from any angle desired. Moreover, the user can convert the graph into an image with a single click. The software installation is straightforward, with an executable link. The Blynk app is used to operate the Raspberry Pi's GPIO remotely. The data is uploaded automatically to the cloud storage without the need to extract the data using a cable. With these two functionalities, an Internet of Things-integrated contactless machine is developed. The ProSight Surface Profiler application is user-friendly, fast, and effortlessly controlled for surface roughness analysis.