LabelSens: Enabling Real-time Sensor Data Labelling at the point of Collection on Edge Computing

by   Kieran Woodward, et al.

In recent years, machine learning has made leaps and bounds enabling applications with high recognition accuracy for speech and images. However, other types of data to which these models can be applied have not yet been explored as thoroughly. In particular, it can be relatively challenging to accurately classify single or multi-model, real-time sensor data. Labelling is an indispensable stage of data pre-processing that can be even more challenging in real-time sensor data collection. Currently, real-time sensor data labelling is an unwieldly process with limited tools available and poor performance characteristics that can lead to the performance of the machine learning models being compromised. In this paper, we introduce new techniques for labelling at the point of collection coupled with a systematic performance comparison of two popular types of Deep Neural Networks running on five custom built edge devices. These state-of-the-art edge devices are designed to enable real-time labelling with various buttons, slide potentiometer and force sensors. This research provides results and insights that can help researchers utilising edge devices for real-time data collection select appropriate labelling techniques. We also identify common bottlenecks in each architecture and provide field tested guidelines to assist developers building adaptive, high performance edge solutions.


page 3

page 5

page 6

page 8


LabelSens: Enabling Real-time Sensor Data Label-ling at the point of Collection on Edge Computing

In recent years, machine learning has made leaps and bounds enabling app...

The complexity of L(p,q)-Edge-Labelling

We classify the complexity of L(p,q)-Edge-k-Labelling in the sense that ...

CDBB West Cambridge Digital Twin: Lessons Learned

The report describes the digital architecture developed for the West Cam...

On-Device Transfer Learning for Personalising Psychological Stress Modelling using a Convolutional Neural Network

Stress is a growing concern in modern society adversely impacting the wi...

MAISON – Multimodal AI-based Sensor platform for Older Individuals

There is a global aging population requiring the need for the right tool...

A Complete LoRaWAN Model for Single-Gateway Scenarios

LoRaWAN is a Low Power Wide Area Network technology featuring long trans...

Please sign up or login with your details

Forgot password? Click here to reset