scholarly journals A Review of Vision-Based On-Board Obstacle Detection and Distance Estimation in Railways

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3452
Author(s):  
Danijela Ristić-Durrant ◽  
Marten Franke ◽  
Kai Michels
Keyword(s):  
Artificial Intelligence ◽  
Research And Development ◽  
Distance Estimation ◽  
Obstacle Detection ◽  
Detection Methods ◽  
Road Vehicles ◽  
Vision Sensors ◽  
Significant Research ◽  
Environment Perception ◽  
Autonomous Detection

This paper provides a review of the literature on vision-based on-board obstacle detection and distance estimation in railways. Environment perception is crucial for autonomous detection of obstacles in a vehicle’s surroundings. The use of on-board sensors for road vehicles for this purpose is well established, and advances in Artificial Intelligence and sensing technologies have motivated significant research and development in obstacle detection in the automotive field. However, research and development on obstacle detection in railways has been less extensive. To the best of our knowledge, this is the first comprehensive review of on-board obstacle detection methods for railway applications. This paper reviews currently used sensors, with particular focus on vision sensors due to their dominant use in the field. It then discusses and categorizes the methods based on vision sensors into methods based on traditional Computer Vision and methods based on Artificial Intelligence.

scholarly journals Night vision obstacle detection and avoidance based on Bio-Inspired Vision Sensors

2020 ◽  
Author(s):  
Jawad N. Yasin ◽  
Sherif A. S. Mohamed ◽  
Mohammad-hashem Haghbayan ◽  
Jukka Heikkonen ◽  
Hannu Tenhunen ◽  
...  
Keyword(s):  
Obstacle Detection ◽  
Night Vision ◽  
Vision Sensors

scholarly journals A Survey on Deep Learning Based Methods and Datasets for Monocular 3D Object Detection

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 517
Author(s):  
Seong-heum Kim ◽  
Youngbae Hwang
Keyword(s):  
Deep Learning ◽  
Object Detection ◽  
Low Cost ◽  
Detection Methods ◽  
Future Research ◽  
3D Object ◽  
Practical Applications ◽  
Depth Sensors ◽  
Significant Research ◽  
3D Object Detection

Owing to recent advancements in deep learning methods and relevant databases, it is becoming increasingly easier to recognize 3D objects using only RGB images from single viewpoints. This study investigates the major breakthroughs and current progress in deep learning-based monocular 3D object detection. For relatively low-cost data acquisition systems without depth sensors or cameras at multiple viewpoints, we first consider existing databases with 2D RGB photos and their relevant attributes. Based on this simple sensor modality for practical applications, deep learning-based monocular 3D object detection methods that overcome significant research challenges are categorized and summarized. We present the key concepts and detailed descriptions of representative single-stage and multiple-stage detection solutions. In addition, we discuss the effectiveness of the detection models on their baseline benchmarks. Finally, we explore several directions for future research on monocular 3D object detection.

Frontier: Autonomy in Detection, Actuation, and Planning for Robotic Weeding Systems

2021 ◽  
Vol 64 (2) ◽  
pp. 557-563
Author(s):  
Piyush Pandey ◽  
Hemanth Narayan Dakshinamurthy ◽  
Sierra N. Young
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Research And Development ◽  
Weed Control ◽  
List Type ◽  
Automated Systems ◽  
Weed Detection ◽  
Detection And Identification ◽  
Key Technologies ◽  
Robotic Weeding

HighlightsRecent research and development efforts center around developing smaller, portable robotic weeding systems.Deep learning methods have resulted in accurate, fast, and robust weed detection and identification.Additional key technologies under development include precision actuation and multi-vehicle planning. Keywords: Artificial intelligence, Automated systems, Automated weeding, Weed control.

scholarly journals SCIENTIFIC AND TECHNOLOGICAL PROBLEMS OF THE DEVELOPMENT OF CYBERSECURITY TECHNOLOGIES ABROAD

2020 ◽  
pp. 169-177
Author(s):  
D.B. Izyumov ◽  
E.L. Kondratyuk
Keyword(s):  
Research And Development ◽  
Department Of Defense ◽  
Smart Devices ◽  
Development Work ◽  
Research Projects ◽  
Regulatory Documents ◽  
The Us ◽  
Significant Research ◽  
Cloud Environments

The article discusses the concept of cybersecurity and its features, presents a list of US regulatory documents in the field of cyberspace and cybersecurity, as well as significant research and development work and programs in the field of development of cybersecurity technologies conducted by the Department of Advanced Research Projects of the US Department of Defense (DARPA). The most common foreign technologies used to protect computers, smart devices, routers, networks and cloud environments, as well as the main scientific and technological problems of the development of cybersecurity technologies, are summarized.

scholarly journals Development and optimization of a portable guidance system for the blind and visually impaired with the application of artificial intelligence

2021 ◽  
Author(s):  
Tamas Nemes
Keyword(s):  
Artificial Intelligence ◽  
Visually Impaired ◽  
Obstacle Detection ◽  
Guidance System ◽  
Performance Standard ◽  
Audio Signals ◽  
Blind And Visually Impaired ◽  
Improve Accuracy ◽  
New Type ◽  
Map Accuracy

This work describes a new type of portable, self-regulating guidance system, which learns to recognize obstacles with the help of a camera, artificial intelligence, and various sensors and thus warn the wearer through audio signals. For obstacle detection, a MobileNetV2 model with an SSD attachment is used which was trained on a custom dataset. Moreover, the system uses the data of motion and distance sensors to improve accuracy. Experimental results confirm that the system can operate with 74.9% mAP accuracy and a reaction time of 0.15 seconds, meeting the performance standard for modern object detection applications. It will also be presented how those affected commented on the device and how the system could be transformed into a marketable product.

scholarly journals Detection of Breast Cancer using AI Techniques – A Survey

2019 ◽  
Vol 7 (7) ◽  
pp. 08-12
Author(s):  
Riju Bhattacharya ◽  
Diksha Gupta ◽  
Divyatara Rathod
Keyword(s):  
Breast Cancer ◽  
Artificial Intelligence ◽  
Cancer Diagnostics ◽  
Detection Methods ◽  
Health Issues ◽  
Process Data ◽  
Mortality And Morbidity ◽  
Medical Progress ◽  
Glass Slides ◽  
Abnormal Cells

Cancer refers to any one of a large number of diseases characterized by the development of abnormal cells that divide uncontrollably and have the ability to infiltrate and destroy normal body tissue.Without treatment, it can cause serious health issues andresult in a loss of life. Breast cancer is the most common cancer among women around the world. Despite enormous medical progress, breast cancer has still remained the second leading cause of death worldwide. Early detection of cancer may reduce mortality and morbidity. This paper presents a review of the detection methods for cancer through Artificial Intelligence (AI) in different ways. Previously Microscopic reviews of tissues on glass slides are used for cancer diagnostics to improve diagnostic accuracy. We can use different techniques such as digital imaging and artificial intelligence algorithm. Cancer care is also advancing thanks to AI’s ability to collect and process data. Due to the nature of processing this information, the task is often a time-consuming and tedious job for doctors. This process may be made much easier, quicker and efficient through the advancement as well as by using modified technologies.

scholarly journals A Literature Review of Performance Metrics of Automated Driving Systems for On-Road Vehicles

2021 ◽  
Vol 2 ◽  
Author(s):  
Mysore Narasimhamurthy Sharath ◽  
Babak Mehran
Keyword(s):  
Motion Planning ◽  
Performance Indicators ◽  
Performance Metrics ◽  
Recent Literature ◽  
Automated Driving ◽  
Road Vehicles ◽  
Multiple Stimulus ◽  
Human Likeness ◽  
Environment Perception ◽  
The Ideal

The article presents a review of recent literature on the performance metrics of Automated Driving Systems (ADS). More specifically, performance indicators of environment perception and motion planning modules are reviewed as they are the most complicated ADS modules. The need for the incorporation of the level of threat an obstacle poses in the performance metrics is described. A methodology to quantify the level of threat of an obstacle is presented in this regard. The approach involves simultaneously considering multiple stimulus parameters (that elicit responses from drivers), thereby not ignoring multivariate interactions. Human-likeness of ADS is a desirable characteristic as ADS share road infrastructure with humans. The described method can be used to develop human-like perception and motion planning modules of ADS. In this regard, performance metrics capable of quantifying human-likeness of ADS are also presented. A comparison of different performance metrics is then summarized. ADS operators have an obligation to report any incident (crash/disengagement) to safety regulating authorities. However, precrash events/states are not being reported. The need for the collection of the precrash scenario is described. A desirable modification to the data reporting/collecting is suggested as a framework. The framework describes the precrash sequences to be reported along with the possible ways of utilizing such a valuable dataset (by the safety regulating authorities) to comprehensively assess (and consequently improve) the safety of ADS. The framework proposes to collect and maintain a repository of precrash sequences. Such a repository can be used to 1) comprehensively learn and model the precrash scenarios, 2) learn the characteristics of precrash scenarios and eventually anticipate them, 3) assess the appropriateness of the different performance metrics in precrash scenarios, 4) synthesize a diverse dataset of precrash scenarios, 5) identify the ideal configuration of sensors and algorithms to enhance safety, and 6) monitor the performance of perception and motion planning modules.

scholarly journals Sole Mate: Safe Path-Finding by Obstacle Detection and Distance Estimation for the Blind

2019 ◽  
Vol 8 (6S4) ◽  
pp. 50-54
Keyword(s):  
Haptic Feedback ◽  
Distance Estimation ◽  
Feedback System ◽  
Obstacle Detection ◽  
Video Footage ◽  
System A ◽  
The World ◽  
Distance Sensor ◽  
Visually Challenged ◽  
Additional Device

The world has increased its demand for assistive technology (AT). There are a lot of researches and developments going on with respect to AT. Among the AT devices which are being developed, the need for a reliable and less expensive device which serves as an assistance for a visually challenged person is in serious demand all around the world. We, therefore, intend to provide a solution for this by constructing a device that has the capability to detect the obstacles within a given range for a visually challenged person and alerting the person about the obstacles. This involves various components like a camera for image detection, an ultrasonic distance sensor for distance estimation and a vibration motor which works on the principle of Haptic feedback and rotates with varied intensities depending on how far the obstacle is from the user. This paper presents a model which is a part of the footwear of the user and hence, no additional device is required to hold onto for assistance. The model involves the use of a microcontroller, a camera, to dynamically perceive the obstacles and a haptic feedback system to alert the person about the same. The camera dynamically acquires the real time video footage which is further processed by the microcontroller to detect the obstacles. Simultaneously, one more algorithm is being executed to estimate the distance with the help of an ultrasonic distance sensor. Depending on the distance, the frequency of the vibration motor, which acts as the output for notifying the user about the obstacle, is varied (haptic feedback). With this system, a visually challenged person will be able to avoid the obstacles successfully without the use of any additional device.

Engineering of Experience Based Trust for E-Commerce

2010 ◽  
pp. 342-367 ◽  
Author(s):  
Zhaohao Sun ◽  
Jun Han ◽  
Dong Dong ◽  
Shuliang Zhao
Keyword(s):  
Artificial Intelligence ◽  
Sustainable Development ◽  
Research And Development ◽  
Multiagent Systems ◽  
System Architecture ◽  
Intelligent Systems ◽  
Multiagent System ◽  
Theoretical Foundation ◽  
Knowledge Based ◽  
Trust Inference

Trust is significant for sustainable development of e-commerce and has received increasing attention in e-commerce, multiagent systems (MAS), and artificial intelligence (AI). However, little attention has been given to the theoretical foundation and intelligent techniques for trust in e-commerce from a viewpoint of intelligent systems and engineering. This chapter will fill this gap by examining engineering of experience-based trust in e-commerce from the viewpoint of intelligent systems. It looks at knowledgebased trust, inference-based trust and their interrelationships with experience-based trust. It also examines scalable trust in e-commerce. It proposes a knowledge based model of trust in e-commerce and a system architecture for METSE: a multiagent system for experience-based trust in e-commerce. The proposed approach in this chapter will facilitate research and development of trust, multiagent systems, e-commerce and e-services.

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