Edge AI devices are low-power systems that have limited computational abilities. These devices make use of machine learning algorithms for analytics and do not completely depend on the cloud for such activities. Edge AI offers innumerable benefits to IoT applications – Reduced latency, improved scalability, enhanced security and minimized strain on the cloud.
Here is an account of another project that was conceptualized at the Embitel Innovation Lab. The engineers developed a ready-to-deploy AIS 140 compliant software stack that can bring about a significant reduction in the development time of a GPS device enabling telematics.
Embitel’s Innovation Lab has recently been abuzz with the development and testing activities related to the DriveSafe app that our engineers have been working on. This app detects driver distractions that can result in road accidents. Powered by a machine learning algorithm, the DriveSafe app analyses driver activities and alerts them of distractions so that they can take corrective action. Learn more about the app here.
In an IoT ecosystem, the cloud is where all the action happens! While designing the database for a cloud application, it is imperative that you consider some key points such as scalability of the solution, data storage requirements, business intelligence/predictive maintenance applications, etc.
Android OS is gaining popularity across industries for embedded systems development. Here are some insights on the advantages of porting Android on IoT-powered In-Vehicle Infotainment Systems, Automotive Head Units and Medical Devices.
Several types of mobile apps can be developed for industrial/enterprise/home automation IoT solutions, based on the project requirements. This page takes a look at each of these in detail.