Video Analytics on IoT devices

02/15/2021
by   Sree Premkumar, et al.
0

Deep Learning (DL) combined with advanced model optimization methods such as RC-NN and Edge2Train has enabled offline execution of large networks on the IoT devices. In this paper, we compare the modern Deep Learning (DL) based video analytics approaches with the standard Computer Vision (CV) based approaches and finally, discuss the best-suited approach for video analytics on IoT devices.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
12/09/2017

Deep Learning for IoT Big Data and Streaming Analytics: A Survey

In the era of the Internet of Things (IoT), an enormous amount of sensin...
research
11/20/2019

REVAMP^2T: Real-time Edge Video Analytics for Multi-camera Privacy-aware Pedestrian Tracking

This article presents REVAMP^2T, Real-time Edge Video Analytics for Mult...
research
06/29/2023

Sustainable Palm Tree Farming: Leveraging IoT and Multi-Modal Data for Early Detection and Mapping of Red Palm Weevil

The Red Palm Weevil (RPW) is a highly destructive insect causing economi...
research
04/20/2022

Multi-Component Optimization and Efficient Deployment of Neural-Networks on Resource-Constrained IoT Hardware

The majority of IoT devices like smartwatches, smart plugs, HVAC control...
research
01/03/2021

Neural Networks for Keyword Spotting on IoT Devices

We explore Neural Networks (NNs) for keyword spotting (KWS) on IoT devic...
research
03/07/2020

Improving IoT Analytics through Selective Edge Execution

A large number of emerging IoT applications rely on machine learning rou...
research
12/11/2021

Automated Customization of On-Thing Inference for Quality-of-Experience Enhancement

The rapid uptake of intelligent applications is pushing deep learning (D...

Please sign up or login with your details

Forgot password? Click here to reset