M-health review: joining up healthcare in a wireless world

In recent years, there has been a huge increase in the use of information and communication technologies (ICT) to deliver health and social care. This trend is bound to continue as providers (whether public or private) strive to deliver better care to more people under conditions of severe budgetary constraint

The Critical Role of Public Charging Infrastructure

Editors: Peter Fox-Penner, PhD, Z. Justin Ren, PhD, David O. JermainA decade after the launch of the contemporary global electric vehicle (EV) market, most cities face a major challenge preparing for rising EV demand. Some cities, and the leaders who shape them, are meeting and even leading demand for EV infrastructure. This book aggregates deep, groundbreaking research in the areas of urban EV deployment for city managers, private developers, urban planners, and utilities who want to understand and lead change

A WI-FI BASED SMART DATA LOGGER FOR CAPSULE ENDOSCOPY AND MEDICAL APPLICATIONS

Wireless capsule endoscopy (WCE) is a non-invasive technology for capturing images of a human digestive system for medical diagnostics purpose. With WCE, the patient swallows a miniature capsule with camera, data processing unit, RF transmitter and batteries. The capsule captures and transmits images wirelessly from inside the human gastrointestinal (GI) tract. The external data logger worn by the patient stores the images and is later on transferred to a computer for presentation and image analysis. In this research, we designed and built a Wi-Fi based, low cost, miniature, versatile wearable data logger. The data logger is used with Wi-Fi enabled smart devices, smart phones and data servers to store and present images captured by capsule. The proposed data logger is designed to work with wireless capsule endoscopy and other biosensors like- temperature and heart rate sensors. The data logger is small enough to carry and conduct daily activities, and the patient do not need to carry traditional bulky data recorder all the time during diagnosis. The doctors can remotely access data and analyze the images from capsule endoscopy using remote access feature of the data logger. Smartphones and tablets have extensive processing power with expandable memory. This research exploits those capabilities to use with wireless capsule endoscopy and medical data logging applications. The application- specific data recorders are replaced by the proposed Wi-Fi data logger and smartphone. The data processing application is distributed on smart devices like smartphone /tablets and data logger. Once data are stored in smart devices, the data can be accessed remotely, distributed to the cloud and shared within networks to enable telemedicine. The data logger can work in both standalone and network mode. In the normal mode of the device, data logger stores medical data locally into a micro Secure Digital card for future download using the universal serial bus to the computer. In network mode, the real-time data is streamed into a smartphone and tablet for further processing and storage. The proposed Wi-Fi based data logger is prototyped in the lab and tested with the capsule hardware developed in our laboratory. The supporting Android app is also developed to collect data from the data logger and present the processed data to the viewer. The PC based software is also developed to access the data recorder and capture and download data from the data logger in real-time remotely. Both in vivo and ex vivo trials using live pig have been conducted to validate the performance of the proposed device

Intelligent Transportation Systems: Fusing Computer Vision and Sensor Networks for Traffic Management

Intelligent Transportation Systems (ITS) represent a pivotal approach to addressing the complex challenges posed by modern-day urban mobility. By seamlessly integrating computer vision and sensor networks, ITS offer a comprehensive solution for traffic management, safety enhancement, and environmental sustainability. This paper delves into the synergistic fusion of computer vision and sensor networks within the framework of ITS, emphasizing their collective role in optimizing traffic flow, mitigating congestion, and enhancing overall road safety. Leveraging cutting-edge technologies such as machine learning, image processing, and Internet of Things (IoT), ITS harness real-time data acquisition and analytics capabilities to facilitate informed decision-making by transportation authorities. Through a comprehensive review of recent advancements, challenges, and opportunities, this paper illuminates the transformative potential of integrating computer vision and sensor networks in ITS. Furthermore, it presents compelling case studies and exemplary applications, showcasing the tangible benefits of this fusion across diverse traffic management scenarios. Ultimately, this paper advocates for the widespread adoption of integrated ITS solutions as a means to usher in a new era of smarter, safer, and more sustainable urban transportation systems

Life Cycle Analysis and Optimization of Wireless Charging Technology to Enhance Sustainability of Electric and Autonomous Vehicle Fleets

The transportation sector is undergoing a major transformation. Emerging technologies play indispensable roles in driving this mobility shift, including vehicle electrification, connection, and automation. Among them, wireless power transfer (WPT) technology, or commonly known as wireless charging technology, is in the spotlight in recent years for its applicability in charging electric vehicles (EVs). On one hand, WPT for EVs can solve some of the key challenges in EV development, by: (1) reducing range anxiety of EV owners by allowing “charging while driving”; and (2) downsizing the EV battery while still fulfilling the same trip distance. More en-route wireless charging opportunities result in battery downsizing, which reduces the high EV price and vehicle weight and improves fuel economy. On the other hand, WPT infrastructure deployment is expensive and resource-intensive, and results in significant economic, environmental, and energy burdens, which can offset these benefits. This research aims to develop and apply a life cycle analysis and optimization framework to examine the role of wireless charging technology in driving sustainable mobility. This research highlights the technology trade-offs and bridges the gap between technology development and deployment by establishing an integrated life cycle assessment and life cycle cost (LCA-LCC) model framework to characterize and evaluate the economic, environmental, and energy performance of WPT EV systems vs. conventional plug-in charging EV systems. Life cycle optimization (LCO) techniques are used to improve the life cycle performance of WPT EV fleets. Based on case studies, this research draws observations and conditions under which wireless charging technology has potential to improve life cycle environmental, energy, and economic performance of electric vehicle fleets. This study begins with developing LCA-LCC and LCO models to evaluate stationary wireless power transfer (SWPT) for transit bus systems. Based on a case study of Ann Arbor bus systems, the wirelessly charged battery can be downsized to 27–44% of a plug-in charged battery, resulting in vehicle lightweighting and fuel economy improvement in the use phase that cancels out the burdens of large-scale infrastructure. Optimal siting strategies of WPT bus charging stations reduced life cycle costs, greenhouse gases (GHG), and energy by up to 13%, 8%, and 8%, respectively, compared to extreme cases of “no charger at any bus stop” and “chargers at every stop”. Next, the LCA-LCC and LCO model framework is applied to evaluate the economic, energy, and environmental feasibility of dynamic wireless power transfer (DWPT) for charging passenger cars on highways and urban roadways. A case study of Washtenaw County indicates that optimal deployment of DWPT electrifying up to about 3% of total roadway lane-miles reduces life cycle GHG emissions and energy by up to 9.0% and 6.8%, respectively, and enables downsizing of the EV battery capacity by up to 48% compared to the non-DWPT scenarios and boosts EV market penetration to around 50% of all vehicles in 20 years. Finally, synergies of WPT and autonomous driving technologies in enhancing sustainable mobility are demonstrated using the LCA framework. Compared to a plug-in charging battery electric vehicle system, a wireless charging and shared automated battery electric vehicle (W+SABEV) system will pay back GHG emission burdens of additional infrastructure deployment within 5 years if the wireless charging utility factor is above 19%.PHDNatural Resources & EnvironmentUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147602/1/bizc_1.pd