AI Core
SenzMatica IoT core platform focuses on all aspects of IoT ecosystems as a one-stop AIoT solutions provider. With the capability to build and customise IoT platforms and smart sensor-based device networks that allow devices to communicate with SenzMatica core services with a high-load, scalable architecture on securely stored data using Big Data, AI, ML, and Deep Learning.
Features of AI Core
IoT Data Pipeline
End to End Pipeline for Machine Learning process of real time IoT Data
Auto ML
Easily build models for IoT and deploy in our platform without any coding
Root cause Analysis
Early identification of defects and faulty conditions in IoT kits and find root cause of the issue
Time series prediction
Predict the future trends using ML and Deep Learning algorithms
Computer Vision
Processing visual data to extract information
Auto Annotation
Annotation tool for easy annotation with ML based auto suggestion
Auto quality testing
Automated quality testing on a huge number of manufactured IoT kits
Defect detection
Auto defect detection capability in images and videos
Feature Comparison Matrix
Auto ML module to build models without any coding
Auto computer vision feature detection
Easily identifies the defects and faulty conditions in any sensors or Edge devices with root cause analysis
Annotation tool for easy annotation.
Processing visual data to generate insights
Predict the future trends with time series prediction using ML and Deep Learning algorithms.
Automated Quality control system for embedded devices
Visual Data based Deep Learning approaches
Forecast future trends with time series prediction
Our SenzMatica AIoT platform analyses large scale sensor data and identifies the potential future Weather Prediction, Price Prediction and Demand Prediction. With the help of big data from the SenzMatica IoT platform and a combination of multiple ML and algorithmic solutions, this module gives an insight into data and future-time-based predictions based on past data. The module helps organisations to predict future trends with greater accuracy.
Computer vision-based defect detection
Using SOTA computer vision models such as image classification , object detection and segmentation , applications are enabled to detect defects and patterns from images.
