Innovative projects co-developed

with partners

at INSAT

Smart manufactory, academic project developed in cooperation with IBM Power AI. Product tracking and counting using Deep Learning, with IBMPowerAI and OpenCV. 

R-CNN is slow because it performs a ConvNet forward pass for each object proposal, without sharing computation The Fast R-CNN method has several advantages:

Higher detection quality (mAP) than R-CNN, SPPnet

Training is single-stage, using a multi-task loss

Training can update all network layers

No disk storage is required for feature caching

LoRaWAN Real-time Environmental Dashboard. 


 

Towards Industry 5.0, Cloud Robotics Platform with IBM Watson AI and Siemens S7-1500. Co-Developed at INSAT.

Vibration monitoring using MEMS accelerometer and IBM Watson rules and actions

Cloud vibration monitoring is emerging as an application that includes two technologies. High performance instruments that monitor machine for maintenance and wireless communication which allows sending data to cloud for monitoring, analyzing and classification.

The vibrations signal measured with an 3-axis MEMS sensor, FFT (Fast Fourier Transform) analysis was performed on STM32 microcontroller then data will be sent to IBM Watson IoT for monitoring, analyzing and classification.

Notification

 

Vibration test

 

Smart Gateway


IoT2040 , first demo Gas detecting : nodered on the #IOT2040 which is equiped with Yocto Linux (open source) and Arduino compatible, the gas sensor is connected directly to #IOT2040 via integrated GPIOx

 

ARM sytem On chip Design 

Cortex M0 based on system on chip With PWM.

Variable duty cycle with assembly code « keil ARM », Pwm module with verilog integrated with ARM M0 SoC
implementation on Nexys 3
Thanks to ARM university program

Touch free sound volume control by stm32 flight sensor over cloud. 

Touch free sound volume control by stm32 flight sensor over cloud#INSAT #Innovation

Posted by Mustapha Hamdi on Tuesday, March 5, 2019