Safety monitoring system of personal mobility driving using deep learning

Safety-Directed System Monitoring Using Safety Cases

Currently, the safety studies of the system (which are also collectively known as the safety case) cease or reduce in their utility after system certification, and with that, a vast amount of knowledge about the failure (or safe) behaviour of the system is usually rendered useless. In this thesis, we argue that this knowledge could be usefully exploited in the context of an appropriate on-line ...

Crop Land Change Monitoring Based on Deep Learning Algorithm Using Multi-temporal Hyperspectral Images

Change detection is done with the purpose of analyzing two or more images of a region that has been obtained at different times which is Generally one of the most important applications of satellite imagery is urban development, environmental inspection, agricultural monitoring, hazard assessment, and natural disaster. The purpose of using deep learning algorithms, in particular, convolutional ...

Object Detection for Autonomous Driving Using Deep Learning

Using driving simulators to assess driving safety.

Changes in drivers, vehicles, and roadways pose substantial challenges to the transportation safety community. Crash records and naturalistic driving data are useful for examining the influence of past or existing technology on drivers, and the associations between risk factors and crashes. However, they are limited because causation cannot be established and technology not yet installed in pro...

Coal Mine Safety Monitoring System Using ARM9

Coal is mined in every country which is mainly used to generate electricity. Thousands of mine workers were killed every year due to many disasters takes place inside coal mine. These accidents are caused mainly due to the leakage of poisonous gas [2] present in the mine. Especially developing countries face a poor safety system for mine workers. Hence it requires a safety monitoring system [1]...