PotSpot: Participatory sensing based monitoring system for pothole detection using deep learning

2021 ◽  
Author(s):  
Susmita Patra ◽  
Asif Iqbal Middya ◽  
Sarbani Roy
Keyword(s):  
Deep Learning ◽  
Monitoring System ◽  
Participatory Sensing ◽  
Pothole Detection

scholarly journals Power Electric Transformer Fault Diagnosis Based on Infrared Thermal Images Using Wasserstein Generative Adversarial Networks and Deep Learning Classifier

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1161
Author(s):  
Kuo-Hao Fanchiang ◽  
Yen-Chih Huang ◽  
Cheng-Chien Kuo
Keyword(s):  
Deep Learning ◽  
Fault Diagnosis ◽  
Monitoring System ◽  
Absolute Difference ◽  
Generative Adversarial Networks ◽  
Economic Losses ◽  
Maintenance Cost ◽  
Full Time ◽  
Noise Interference ◽  
In Series

The safety of electric power networks depends on the health of the transformer. However, once a variety of transformer failure occurs, it will not only reduce the reliability of the power system but also cause major accidents and huge economic losses. Until now, many diagnosis methods have been proposed to monitor the operation of the transformer. Most of these methods cannot be detected and diagnosed online and are prone to noise interference and high maintenance cost that will cause obstacles to the real-time monitoring system of the transformer. This paper presents a full-time online fault monitoring system for cast-resin transformer and proposes an overheating fault diagnosis method based on infrared thermography (IRT) images. First, the normal and fault IRT images of the cast-resin transformer are collected by the proposed thermal camera monitoring system. Next is the model training for the Wasserstein Autoencoder Reconstruction (WAR) model and the Differential Image Classification (DIC) model. The differential image can be acquired by the calculation of pixel-wise absolute difference between real images and regenerated images. Finally, in the test phase, the well-trained WAR and DIC models are connected in series to form a module for fault diagnosis. Compared with the existing deep learning algorithms, the experimental results demonstrate the great advantages of the proposed model, which can obtain the comprehensive performance with lightweight, small storage size, rapid inference time and adequate diagnostic accuracy.

scholarly journals A Real-time Pothole Detection Based on Deep Learning Approach

2021 ◽  
Vol 1828 (1) ◽  
pp. 012001
Author(s):  
Yeoh Keng Yik ◽  
Nurul Ezaila Alias ◽  
Yusmeeraz Yusof ◽  
Suhaila Isaak
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Learning Approach ◽  
Pothole Detection

scholarly journals Segmentation of Affected Crops using Deep Learning

2019 ◽  
Vol 8 (5S3) ◽  
pp. 232-234
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Monitoring System ◽  
Learning Algorithm ◽  
Target Area ◽  
Learning Technology ◽  
Machine Learning Algorithm ◽  
Normal Human ◽  
Human Monitoring ◽  
Disease Attack

Deep Learning technology can accurately predict the presence of diseases and pests in the agricultural farms. Upon this Machine learning algorithm, we can even predict accurately the chance of any disease and pest attacks in future For spraying the correct amount of fertilizer/pesticide to elimate host, the normal human monitoring system unable to predict accurately the total amount and ardent of pest and disease attack in farm. At the specified target area the artificial percepton tells the value accurately and give corrective measure and amount of fertilizers/ pesticides to be sprayed.

A Vision-Based Hygiene Monitoring System: Using Deep Learning to Assess Handwashing Procedure in Real Time

2019 ◽  
Author(s):  
Maria Galkin ◽  
Kashmala Rehman ◽  
Benjamin Schornstein ◽  
Warren Sunada-Wong ◽  
Harvey Wang
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Monitoring System

A Deep Learning Approach for Speed Bump and Pothole Detection Using Sensor Data

2021 ◽  
pp. 73-85
Author(s):  
Bharani Ujjaini Kempaiah ◽  
Ruben John Mampilli ◽  
K. S. Goutham
Keyword(s):  
Deep Learning ◽  
Sensor Data ◽  
Learning Approach ◽  
Pothole Detection
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