SenzMatica AIoT Platform
Is an end-to-end integrated platform
Lets you connect billions of IoT Devices and route trillions of AI possibilities
SenzMatica Platform Architecture
SenzMate's Products Trusted By Big Company
IoT Kits
Revolutionize Your Business with Our Industry-Specific IoT Kits
IoT Kits
Revolutionize Your Business with Our Industry-Specific IoT Kits
IoT Kits assist you connect devices with visual and sensor input streams, capture data via wireless networks and provide intelligence to the edge while securely upgrading insights to the cloud for further processing.
Sensors of IoT Kits
Connect with sensor and visual inputs
IoT Data Processing
Process the raw input and identify the real world facts
Power consumption
Power estimation in multi-socket systems
Sensor calibration
High performing Remote calibrations to keep data accurate
IoT Core
Innovate Faster with Our Modular
and Customizable IoT Core
SenzMatica IoT core focuses on every key component to manage AIoT applications with capabilities to manage millions of connected devices with a high-load, scalable architecture to derive insights from securely stored Big Data through AI, ML, and Deep Learning.
User management
Dynamic access control features based on user roles.
Load Balancer
Manage and control millions of connected smart devices simultaneously.
Remote configuration
Connect and setup your widely dispersed IoT devices remotely.
Data protection
Security-enhanced environment for sending and receiving data from IoT devices.
AI Core
Get smart insights from the IoT data with AI
AI Core processes the sensor and visual data inputs from the deployed IoT Kits and visualises the data to deliver vital real-time information for customers to uncover new opportunities. Data generated from IoT kits can be analysed using machine learning and data analytics to find patterns to extract insights.
IoT Data Pipeline
End to End Pipeline for Machine Learning process of real time IoT Data
Defect detection
Auto defect detection capability in images and videos
Auto quality testing
Automated quality testing on a huge number of manufactured IoT kits
Quick IoT ML platform
Easy-to-use web-based ML platform for IoT
Feature Comparison Matrix
IoT Kits
Connecting with sensor inputs
Computer vision based inputs
Processing the sensor raw input to identify the real world facts
Analyzing the visual raw data to discover the real world insights
Communicating with other Edges in the RF wireless network
Interacting with other Edges in the LoRa wireless network
Power optimization in the Edge
Advanced Security mechanisms in the Edge
Building Intelligence in the Edge
Communicating with cloud servers via 2G,3G, WiFi
Cloud communicating via 4G, NBioT
Basic Firmware Libraries
Premium Firware Libraries
Integration with Over the air update
Customized Circuit and PCB Design
Device Manufacturing Processes
Remote Calibration module
Getting Certification
IoT Core
Manage and control millions of connected smart devices simultaneously
Dynamic access control features based on user roles
Transport data between servers and various connected devices via HTTP protocols
Data transfers between various IoT devices and servers using MQTT protocols
Real time data process, basic analytics for exploration and optimization [Eg : Anomalies]
Real-time failure prediction using deep analytics
Remote configuration settings on connected devices
Over-the-air update deployment
Real time sensor data streaming on IoT data
Visual data streaming in real time on IoT data
Bulk Data analytic framework
Basic Security for sending and receiving data from IoT devices
AES Encryption, SSL intregrated security-enhanced enviornment for data protection
AI Core
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
Predict the future trends with time series prediction using ML and Deep Learning algorithms.
Processing visual data to generate insights
Annotation tool for easy annotation
Automated Quality control system for embedded devices
Visual Data based Deep Learning approaches