Otimização do consumo de bateria em hardware de internet das coisas industrial

Abstract

Electrical Engineering offers a wide area of expertise, regarding not only to solving problems in the field of electricity, electronics, control and automation, but also relates to everything that is being currently migrated to the "cloud", with an innovative digitalization technology. In the 21st century, the Internet of Things has improved its performance and thus, the usage of monitoring equipment has improved in applications for both personal use and industrial solutions. The industrial startup TRACTIAN, created in 2019, develops and markets remote sensing devices, which operate connected to the power grid or baterry, and also offers a software platform that shall process and present the information. This sensor collects vibration and temperature data from machines operating in industrial environments and forwards them to TRACTIAN’s digital platform, where the use of artificial intelligence and machine learning techniques are applied to identify possible failures in machinery, before they are completely damaged or broken. The primary goal of this work is to identify a possibility of decrease in the device’s battery consumption, and for that two main optimizations were applied: decrease in the amount of information sent from the sensor to a wireless network, as a result of a change in its internal processing still in the hardware, and another decrease in the access time to the microprocessor’s memory to obtain the data to be sent. From these two changes, it was possible to identify decreases not only in the duration of each operation cycle of the sensor, but also in the amount of current consumed per cycle. Therefore, its baterry will last longer and the product will have a greater potential in the market.