bharathsudharsan

TinyML-CAM

Code for MobiCom paper 'TinyML-CAM: 80 FPS Image Recognition in 1 Kb RAM'

ML-MCU

Code for IoT Journal paper 'ML-MCU: A Framework to Train ML Classifiers on MCU-based IoT Edge Devices'

TinyML-Benchmark-NNs-on-MCUs

Code for WF-IoT paper 'TinyML Benchmark: Executing Fully Connected Neural Networks on Commodity Microcontrollers'

CNN_on_MCU

Code for paper 'Multi-Component Optimization and Efficient Deployment of Neural-Networks on Resource-Constrained IoT Hardware'

Train_plus_plus

Code for paper 'Train++: An Incremental ML Model Training Algorithm to Create Self-Learning IoT Devices'

COVID-away

Code for paper 'Avoid touching your face: A hand-to-face 3d motion dataset (covid-away) and trained models for smartwatches'

Edge2Guard

Code for PerCom paper 'Edge2Guard: Botnet Attacks Detecting Offline Models for Resource-Constrained IoT Devices'

OTA-TinyML

Code for IEEE Internet Computing Journal paper 'OTA-TinyML: Over the Air Deployment of TinyML Models and Execution on IoT Devices'

ML-Classifiers-on-MCUs

Supplementary material for IEEE Services Computing paper 'An SRAM Optimized Approach for Constant Memory Consumption and Ultra-fast Execution of ML Classifiers on TinyML Hardware'

Alexa-Smart-Speaker

A modern Smart-speaker with an advanced microphone array, camera module interfaced with Pi capable of performing AI-based tasks

profile

Link: https://bharathsudharsan.github.io/profile/

AVRGait

Optimized-One-vs-One-Algorithm

Code for AAAI poster 'Training up to 50 Class ML Models on 3 $ IoT Hardware via Optimizing One-vs-One Algorithm'

Edge2Train

Code for IoT paper 'Edge2Train: a framework to train machine learning models (SVMs) on resource-constrained IoT edge devices'

Air-Quality-IoT-Analytics

Repo and code of the UbiComp-ISWC 2021 paper: 'Air Quality Sensor Network Data Acquisition, Cleaning, Visualization, and Analytics: A Real-world IoT Use Case'

ECML-Tutorial-ML-Meets-IoT

Repository of the ECML PKDD 2021 tutorial title 'Machine Learning Meets Internet of Things: From Theory to Practice'

ML-Model-Combining

Code for BigData paper 'Ensemble Methods for Collective Intelligence: Combining Ubiquitous ML Models in IoT'

Reducing-Overprocessing-of-DNNs

Tiny-Impute

On-device Hybrid Anomaly Detection and Data Imputation