Development of low cost autonomous wheelchair using gps for outdoor purposes

Electric wheelchair has been widely used to facilitate and minimize the user’s effort to move independently. Users prefer to control the movement of the wheelchair on their own without any assistance. Although electric wheelchairs are considered a good solution to minimise the effort in independently moving the wheelchair, but unfortunately, electric wheelchairs are expensive in Malaysia. Moreover, most of the available electric wheelchairs in the market use only the joystick as control device. However, the joystick is not suitable for most cases. For example, blind users, users with mental disorders or with both hands paralyzed, are unable to hold and control the joystick. Such users still need to be assisted by others. However, other people will not always be available to help due to any constraints. Using other means of control devices may partially solve the issues but may not be entirely resolved. Therefore, wheelchair needs some improvement utilising smarter and low cost control system that can resolve some critical cases for example the users that are unable to use both their hands and legs. This research main focuses on developing a control system to allow wheelchairs to move autonomously from one point to another using Global Positioning System (GPS) while saving the cost to make it affordable for the users. The main problem in building an autonomous system is the accuracy and consistency of GPS reading. To solve that problem a simple algorithm is developed to improve the accuracy in positioning and path planning for the wheelchair. The averaging technique was applied in positioning to improve the accuracy and consistency of the GPS reading. The GPS positioning becomes more accurate as the averaging technique reduced the GPS reading to two consistent readings instead of five different readings. In terms of accuracy, the distance between the actual point and the GPS measured point had decreased from 4 meters to only 3 meters. The stop angle was adjusted by changing the setting for the stop angle’s constant because the wheelchair does not immediately stop at the desired turning point due to the Law of Inertia. The value of that constant has to be experimentally set according to error in turning angle. The suggested solution is by integrating rotary encoder with the compass. The constant kp= 60 pulses was applied in straight movement correction, and can be seen that the wheels always trying to balance each other. Experiments have been conducted to test the ability of the system and fulfil the task of reaching a pre-stated destination accurately. This wheelchair can be used for outdoor movement as the GPS is more accurate outside of the building. For instance, the users want to go to the nearest clinic or park within 1 kilometre from their home. This will save time as they don’t need to wait to seek for assistance

Image processing techniques for the detection and characterisation of features and defects in railway tracks

This thesis describes the research that led to the development of a machine vision system in collaboration with TATA, UK and Sheffield Supertram. This was part of a European initiative for Predictive Maintenance employing non-intrusive inspection and data analysis known as PM’n’Idea. The hardware and software design, construction, and evaluation of a prototype for predictive maintenance are presented. The prototype was tested on Sheffield and Warsaw’s tram systems. The prototype has been designed with due account of a specified set of environmental constraints such as a high level of vibrations and space restrictions of the target trams. Special computer vision techniques have been specifically developed to be used with the prototype. Various image processing techniques and algorithms have been evaluated for the purpose of detection and characterisation of a series of rail abnormalities and faults. The system described in this thesis makes use of a number of standard and modified image processing techniques, not only to alleviate the requirements for manual inspections, but also to allow continuous monitoring and tracking of any defects or abnormalities in a rail track. Currently, detecting defects in their earlier stages can only be achieved by using close visual inspection i.e. line walking. Extensive testing and evaluation of the performance of the prototype inspection system at Sheffield Supertram indicated that the system was able to detect abnormalities with a resolution down to 0.1 mm. Evidence of the classification rates for the standard and modified algorithms that are implemented in the system are presented in this thesis. The algorithms developed show an average success rate of 88.9% in detecting surface bound abnormalities

EG-ICE 2021 Workshop on Intelligent Computing in Engineering

The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways

EG-ICE 2021 Workshop on Intelligent Computing in Engineering

The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways

Novel Approaches for Structural Health Monitoring

The thirty-plus years of progress in the field of structural health monitoring (SHM) have left a paramount impact on our everyday lives. Be it for the monitoring of fixed- and rotary-wing aircrafts, for the preservation of the cultural and architectural heritage, or for the predictive maintenance of long-span bridges or wind farms, SHM has shaped the framework of many engineering fields. Given the current state of quantitative and principled methodologies, it is nowadays possible to rapidly and consistently evaluate the structural safety of industrial machines, modern concrete buildings, historical masonry complexes, etc., to test their capability and to serve their intended purpose. However, old unsolved problematics as well as new challenges exist. Furthermore, unprecedented conditions, such as stricter safety requirements and ageing civil infrastructure, pose new challenges for confrontation. Therefore, this Special Issue gathers the main contributions of academics and practitioners in civil, aerospace, and mechanical engineering to provide a common ground for structural health monitoring in dealing with old and new aspects of this ever-growing research field

Control Theory in Engineering

The subject matter of this book ranges from new control design methods to control theory applications in electrical and mechanical engineering and computers. The book covers certain aspects of control theory, including new methodologies, techniques, and applications. It promotes control theory in practical applications of these engineering domains and shows the way to disseminate researchers’ contributions in the field. This project presents applications that improve the properties and performance of control systems in analysis and design using a higher technical level of scientific attainment. The authors have included worked examples and case studies resulting from their research in the field. Readers will benefit from new solutions and answers to questions related to the emerging realm of control theory in engineering applications and its implementation

Applied Metaheuristic Computing

For decades, Applied Metaheuristic Computing (AMC) has been a prevailing optimization technique for tackling perplexing engineering and business problems, such as scheduling, routing, ordering, bin packing, assignment, facility layout planning, among others. This is partly because the classic exact methods are constrained with prior assumptions, and partly due to the heuristics being problem-dependent and lacking generalization. AMC, on the contrary, guides the course of low-level heuristics to search beyond the local optimality, which impairs the capability of traditional computation methods. This topic series has collected quality papers proposing cutting-edge methodology and innovative applications which drive the advances of AMC

Context-Enabled Visualization Strategies for Automation Enabled Human-in-the-loop Inspection Systems to Enhance the Situation Awareness of Windstorm Risk Engineers

Insurance loss prevention survey, specifically windstorm risk inspection survey is the process of investigating potential damages associated with a building or structure in the event of an extreme weather condition such as a hurricane or tornado. Traditionally, the risk inspection process is highly subjective and depends on the skills of the engineer performing it. This dissertation investigates the sensemaking process of risk engineers while performing risk inspection with special focus on various factors influencing it. This research then investigates how context-based visualizations strategies enhance the situation awareness and performance of windstorm risk engineers. An initial study investigated the sensemaking process and situation awareness requirements of the windstorm risk engineers. The data frame theory of sensemaking was used as the framework to carry out this study. Ten windstorm risk engineers were interviewed, and the data collected were analyzed following an inductive thematic approach. The themes emerged from the data explained the sensemaking process of risk engineers, the process of making sense of contradicting information, importance of their experience level, internal and external biases influencing the inspection process, difficulty developing mental models, and potential technology interventions. More recently human in the loop systems such as drones have been used to improve the efficiency of windstorm risk inspection. This study provides recommendations to guide the design of such systems to support the sensemaking process and situation awareness of windstorm visual risk inspection. The second study investigated the effect of context-based visualization strategies to enhance the situation awareness of the windstorm risk engineers. More specifically, the study investigated how different types of information contribute towards the three levels of situation awareness. Following a between subjects study design 65 civil/construction engineering students completed this study. A checklist based and predictive display based decision aids were tested and found to be effective in supporting the situation awareness requirements as well as performance of windstorm risk engineers. However, the predictive display only helped with certain tasks like understanding the interaction among different components on the rooftop. For remaining tasks, checklist alone was sufficient. Moreover, the decision aids did not place any additional cognitive demand on the participants. This study helped us understand the advantages and disadvantages of the decision aids tested. The final study evaluated the transfer of training effect of the checklist and predictive display based decision aids. After one week of the previous study, participants completed a follow-up study without any decision aids. The performance and situation awareness of participants in the checklist and predictive display group did not change significantly from first trial to second trial. However, the performance and situation awareness of participants in the control condition improved significantly in the second trial. They attributed this to their exposure to SAGAT questionnaire in the first study. They knew what issues to look for and what tasks need to be completed in the simulation. The confounding effect of SAGAT questionnaires needs to be studied in future research efforts