A study of smart device-based mobile imaging and implementation for engineering applications

Title from PDF of title page, viewed on June 12, 2013Thesis advisor: ZhiQiang ChenVitaIncludes bibliographic references (pages 76-82)Thesis (M.S.)--School of Computing and Engineering. University of Missouri--Kansas City, 2013Mobile imaging has become a very active research topic in recent years thanks to the rapid development of computing and sensing capabilities of mobile devices. This area features multi-disciplinary studies of mobile hardware, imaging sensors, imaging and vision algorithms, wireless network and human-machine interface problems. Due to the limitation of computing capacity that early mobile devices have, researchers proposed client-server module, which push the data to more powerful computing platforms through wireless network, and let the cloud or standalone servers carry out all the computing and processing work. This thesis reviewed the development of mobile hardware and software platform, and the related research done on mobile imaging for the past 20 years. There are several researches on mobile imaging, but few people aim at building a framework which helps engineers solving problems by using mobile imaging. With higher-resolution imaging and high-performance computing power built into smart mobile devices, more and more imaging processing tasks can be achieved on the device rather than the client-server module. Based on this fact, a framework of collaborative mobile imaging is introduced for civil infrastructure condition assessment to help engineers solving technical challenges. Another contribution in this thesis is applying mobile imaging application into home automation. E-SAVE is a research project focusing on extensive use of automation in conserving and using energy wisely in home automation. Mobile users can view critical information such as energy data of the appliances with the help of mobile imaging. OpenCV is an image processing and computer vision library. The applications in this thesis use functions in OpenCV including camera calibration, template matching, image stitching and Canny edge detection. The application aims to help field engineers is interactive crack detection. The other one uses template matching to recognize appliances in the home automation system.Introduction -- Background and related work -- Basic imaging processing methods for mobile applications -- Collaborative and interactive mobile imaging -- Mobile imaging for smart energy -- Conclusion and recommendation

An online environmental approach to service interaction management in home automation

Home automation is maturing with the increased deployment of networks and intelligent devices in the home. Along with new protocols and devices, new software services will emerge and work together releasing the full potential of networked consumer devices. Services may include home security, climate control or entertainment. With such extensive interworking the phenomenon known as service interaction, or feature interaction, appears. The problem occurs when services interfere with one another causing unexpected or undesirable outcomes. The main goal of this work is to detect undesired interactions between devices and services while allowing positive interactions between services and devices. If the interaction is negative, the approach should be able to handle it in an appropriate way. Being able to carry out interaction detection in the home poses certain challenges. Firstly, the devices and services are provided by a number of vendors and will be using a variety of protocols. Secondly, the configuration will not be fixed, the network will change as devices join and leave. Services may also change and adapt to user needs and to devices available at runtime. The developed approach is able to work with such challenges. Since the goal of the automated home is to make life simpler for the occupant, the approach should require minimal user intervention. With the above goals, an approach was developed which tackles the problem. Whereas previous approaches solving service interaction have focused on the service, the technique presented here concentrates on the devices and their surrounds, as some interactions occur through conflicting effects on the environment. The approach introduces the concept of environmental variables. A variable may be room temperature, movement or perhaps light. Drawing inspiration from the Operating Systems domain, locks are used to control access to the devices and environmental variables. Using this technique, undesirable interactions are avoided. The inclusion of the environment is a key element of this approach as many interactions can happen indirectly, through the environment. Since the configuration of a home’s devices and services is continually changing, developing an off-line solution is not practical. Therefore, an on-line approach in the form of an interaction manager has been developed. It is the manager’s role to detect interactions. The approach was shown to work successfuly. The manager was able to successfully detect interactions and prevent negative interactions from occurring. Interactions were detected at both device and service level. The approach is flexible: it is protocol independent, services are unaware of the manager, and the manager can cope with new devices and services joining the network. Further, there is little user intervention required for the approach to operate.EThOS - Electronic Theses Online ServiceGBUnited Kingdo