Hands on AIoT
Dive into demos that showcase capabilities of the Shunya AIoT.
43 Demos
Robotic Arm trained to detect objects and sort them by pick and place.
Recognizes face and operates Robotic Arm to give out cards.
Face Mask Detection for COVID-19 safety measures on live Footage.
Unlock door using Face-Recognition on 10 USD embedded device.
Sends SMS and Whatsapp alerts to the manager when parameters cross the thresholds.
Mainly used as an HMI interface on factory floors. Ability to create low cost embedded devices with touch functionally and beautiful dashboards
Application of Logistic regression on Industrial boiler data to predict faults in Textile production. All of this displayed as a Dashboard.
Shunya AI runs on Edge (Raspberry Pi 4) with minimal os and minimal web interface.
Detects faces despite the person wearning face masks on CCTV video feed.
Shows the Capability to Detect multiple faces in a Video while Running on Edge.
Detects Common household Objects in a video while running on Edge.
Embedded device(kiosk) which can display ads based on age/gender
Using AI to calculate TRP and check the emotions of a Person watching TV.
Scans the BSNL electricity bill and give Due Date and Amount Payable in excel.
IoT Dashboard for farms using ThingsBoard platform for Data visualisation, Alarms and Device Management.
Program your IoT device using IEC 61131 supported programming Languages using Shunya OS.
Get alert on unusual baby activities like if baby is crying or baby is using the computer.
Getting License plate number using Number plate detection and recognition.
Industrial IoT Gateway with Global 3G/4G LTE connectivity for remote deployment. And GNSS/GPS support for Asset Management and Tracking.
Once learnt, webscrapperOCR automatically search the website, takes screenshot and extract the information from it and store it in excel using OCR.
Shunya IoT gateway supports S7 protocol which can be used to read data from Siemens PLC's and send the data to the Cloud.
Takes video/camera stream as an input and recognizes human activities such as running and jumping.
Takes seven segment image and gives the number output on text format.
Detecting Anomaly Cells from Miscropy images with basic image processing techniques.
This method uses basic image processing techniques to implement ID card detection and cropping.