Artificial intelligence-based spatio-temporal vision sensors: applications and prospects

Abstract

Introduction: Advances in machine vision and mobile electronics will be accelerated by the creation of sophisticated optoelectronic vision sensors that allow for sophisticated picture recognition of visual information and data pre-processing. Several new types of vision sensors have been devised in the last decade to solve these drawbacks, one of which is neuromorphic vision sensors, which have exciting qualities such as high temporal resolution, broad dynamic range, and low energy consumption. Neuromorphic sensors are inspired by the working principles of biological sensory neurons and would be useful in telemedicine, health surveillance, security monitoring, automatic driving, intelligent robots, and other applications of the Internet of Things.Methods: This paper provides a comprehensive review of various state-of-the-art AI vision sensors and frameworks.Results: The fundamental signal processing techniques deployed and the associated challenges were discussed.Discussion: Finally, the role of vision sensors in computer vision is also discussed.

Clayshock mechanism and application to shield tunneling through existing tunnels: Settlement prediction using artificial intelligence

“…Consequently, many researchers have employed neural network prediction models to predict different aspects of the shield construction process. These aspects encompass the tunneling performance of the shield machine [8][9][10][11], the occurrence of abnormal equipment faults [12,13], and the extent of cutter wear [14,15]. The use of this model has yielded favorable outcomes in terms of prediction accuracy.…”