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AIoT

Keywords from Day 5 of Online Workshop on Development and Deployment of AIoT based solution for Industrial Applications by NSUT, Delhi

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Further to Day 1 & 2 / Day 3 & 4 keywords posted in the past as per the links here, below are the keywords for Day 5: Keywords from Day 1 & 2 of Online Workshop on Development and Deployment of AIoT based solution for Industrial Applications by NSUT, Delhi | LinkedIn, Keywords from Day 3 & 4 of Online Workshop on Development and Deployment of AIoT based solution for Industrial Applications by NSUT, Delhi | LinkedIn:

Session 1:

Speakers:

Dr. Sudeepta Mishra | Department of Computer Science & Engineering (iitrpr.ac.in)

Sudeepta Mishra | LinkedIn

Raushan Kumar Singh | LinkedIn

Keywords:

TinyML 

MicroControllers and it’s advantages in IoT / AIoT

Hardware Software Co-design 

Hacking / confusing signals to IoT / Electromagnetic Pulses  

Internet of Battlefield Things (IoBT) 

Sensor hacking 

Use case for border fencing security 

Hand gesture recognition practical 

www.EdgeImpulse.com – Build datasets, train models, and optimize libraries to run directly on device; from the smallest microcontrollers to gateways with the latest neural accelerators (and anything in between).

Programming on TinyML

Compressing models 

Sin wave generation and detection on TinyML 

On-Device Training with TensorFlow Lite

TensorFlow Lite for Microcontrollers 

TensorFlow Lite 

Hex file for microcontroller – header file 

EloquentTinyML library 

Arduino

Raspberry Pi

Wokwi – Online ESP32, STM32, Arduino Simulator 

Training your model and putting it directly in firmware

Quantization in TinyML

Session 2:

Speakers:

Prof. SRN Reddy – DIC-IGDTUW 

CSE (igdtuw.ac.in) 

Keywords:

Practical approach to Smart IoT devices 

ARM processor 

Peripherals

Embedded and IoT devices differences

Framework of Smart IoT – Smartphone

Jetson Nano NVidia

Hardware components for smart IoT / SmartPhone

My_OS

Commercialization of Smart IoT

Smart Healthcare product

Aquaculture product

Challenges with Aquaculture product – Scaling, reactions with water of sensors & dirty solar panels

Environmental monitoring system

Various MTech / PhD thesis discussion & demos for prototypes & products

ETI Labs Pvt. Ltd.

Various boards for Arduino, 8051 and products / kits on top of it

Instrumentation for above

Industry 4.0 testbed

Button marking & stitching machine – autonomous system

AIoT in agriculture – Temperature, Humidity, CO2 & AQI monitoring

Drone with multi-spectral imaging for farming for NPK (Nitrogen, phosphorus, and potassium) monitoring with AI

Production monitoring with AIoT

AIoT

Keywords from Day 1 & 2 of Online Workshop on Development and Deployment of AIoT based solution for Industrial Applications by NSUT, Delhi

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Attending online “Five Days SERB sponsored Workshop on Development and Deployment of AIoT based solution for Industrial Applications” from 17th-21st June 2024

Organized by:

Dept. of Computer Science & Engineering

Netaji Subhas University of Technology, Delhi

110078, India

www.nsut.ac.in

Following Topics will be covered during the program.

• Introduction to AIoT, Sensors, AIoT Use Cases.

• Artificial Intelligence: A requirement for IoT

• Deployment for Raspberry PI

• Machine Learning for IoT, ML on IoT Data

• Deep Learning: A Review, Transfer learning for AIoT

• Deployment of ML/DL models over Web

• Federated Learning based Air pollution Monitoring

• IoT Security: Countermeasures

• Deploying DL model on Edge Devices

• An Assistive Solution for Visually Impaired

• Comparison of Edge Devices for AIoT Deployment

• Research Possibilities and Future Directions

https://drive.google.com/file/d/1UjWlSlhZJ-xZxAe5wtEAfVl-OCYrOOPK/view – Poster link

Keywords:

Day 1:

  • Grounding in LLMs
  • Fashion industry use case for AI
  • Licensed vs. unlicensed spectrum in India
  • https://edgeimpulse.com/ – LoRaWAN, LoRa – AIoT example
  • Elaboration of architecture for AIoT protocol LoRa and LoRaWAN deployed at one of the IITs plus fashion industry usecase

Day 2:

AIoT network simulation:

Automatic speech recognition:

  • Phonemes vs Morphemes
  • Disadvantages of traditional cascade models – errors are amplified
  • MFCC
  • LSTM
  • End to end model
  • Hugging face
  • Whisper model

Speakers: