Akpo, Eugenia Mawuenya2023-05-092023-05-092021-05https://hdl.handle.net/20.500.11988/859Capstone Project submitted to the Department of Engineering, Ashesi University in partial fulfillment of the requirements for the award of Bachelor of Science degree in Computer Engineering, May 2021Electrical machines are heavily used in industry today as they form an integral part of the production. In the occurrence of a breakdown, processing and production are delayed hence the importance of motor condition monitoring. Unfortunately, manual condition monitoring techniques are not entirely reliable. IoT emergence proves to be reliable and decreases downtime in the daily use of the induction motor. In this project, an IoT platform is built using Bluetooth technology, temperature, current, voltage and accelerometer sensors for data collection, storing data on the cloud and building a machine learning model to predict faults based on prevalent faults diagnosis techniques on induction.enmachine monitoringfault detectionCapstone project