This paper summarizes the state of the art in connected vehicles--from the need for vehicle data and applications thereof, to enabling technologies, challenges, and identified opportunities. Connectivity is increasing around the world and its expansion to vehicles is no exception. With improvements in connectivity, sensing, and computation, the future will see vehicles used as development platforms capable of generating rich data, acting based on inference, and effecting great change in transportation, the human-vehicle dynamic, the environment, and the economy. Connected vehicle technologies have already been used to improve fleet safety and efficiency, with emerging technologies additionally allowing data to be used to inform aspects of vehicle design, ownership, and use. While the demand for connected vehicles and its enabling technology has progressed significantly in recent years, there remain challenges to connected and collaborative vehicle application deployment before the full potential of connected cars may be realized. From extensibility and scalability to privacy and security, this paper informs the reader about key enabling technologies, opportunities, and challenges in the connected vehicle landscape.

Path planning algorithms are used by mobile robots, unmanned aerial vehicles, and autonomous cars in order to identify safe, efficient, collision-free, and least-cost travel paths from an origin to a destination. Choosing an appropriate path planning algorithm helps to ensure safe and effective point-to-point navigation, and the optimal algorithm depends on the robot geometry as well as the computing constraints, including static/holonomic and dynamic/non-holonomically-constrained systems, and requires a comprehensive understanding of contemporary solutions. The goal of this paper is to help novice practitioners gain an awareness of the classes of path planning algorithms used today and to understand their potential use cases—particularly within automated or unmanned systems. To that end, we provide broad, rather than deep, coverage of key and foundational algorithms, with popular algorithms and variants considered in the context of different robotic systems. The definitions, summaries, and comparisons are relevant to novice robotics engineers and embedded system developers seeking a primer of available algorithms.

The Internet of Things' (IoT's) rapid growth is constrained by resource use and fears about privacy and security. A solution jointly addressing security, efficiency, privacy, and scalability is needed to support continued expansion. We propose a solution modeled on human use of context and cognition, leveraging cloud resources to facilitate IoT on constrained devices. We present an architecture applying process knowledge to provide security through abstraction and privacy through remote data fusion. We outline five architectural elements and consider the key concepts of the “data proxy” and the “cognitive layer.” The data proxy uses system models to digitally mirror objects with minimal input data, while the cognitive layer applies these models to monitor the system's evolution and to simulate the impact of commands prior to execution. The data proxy allows a system's sensors to be sampled to meet a specified quality of data target with minimal resource use. The efficiency improvement of this architecture is shown with an example vehicle tracking application. Finally, we consider future opportunities for this architecture to reduce technical, economic, and sentiment barriers to the adoption of the IoT.

There is an opportunity to utilize wearable, consumer-oriented sensors for self-health monitoring and preventative medicine. Disposable diaper with built-in low-cost, disposable moisture sensors is one such product. Diaper users include infants, elderly, disabled individuals, and hospital patients. Event-based alerting can enhance care of this population by improving incontinence management, preventing rashes and infections, and avoiding embarrassment. Collected data can be used to optimize change intervals, thereby reducing waste and expense. In this article, we realize a novel disposable sensor for moisture detection leveraging the material properties of the water absorbing polymer gel common to most diapers. We demonstrate a functional UHF RFID moisture monitor based on hydrogel sensing and propose a hybrid sensor design utilizing metal and hydrogel optimized for a specific diaper geometry. The proposed sensor design achieves a 1-meter read range, a bend radius of <20mm, is insensitive to sensor orientation relative to the reader, and is lower-cost than sensors with metallic antennas. We detail design considerations for integration with manufacturing processes and conclude by exploring possible future applications enabled by hydrogel sensing.

Digital twins are expected to form a network, a “Digital Twin Web,” in the future. Digital Twin Web follows a similar structure to the World Wide Web and consists of meta-level digital twins that are described as digital twin description documents and distributed via Digital Twin Web servers. Standards must be established before the Digital Twin Web can be used efficiently, and having an easily accessible server implementation can foster the development of those standards. Twinbase is an open-source, Git-based Digital Twin Web server developed with user-friendliness in mind. Twinbase stores digital twin documents in a Git repository, modifies them with Git workflows, and distributes them to users via a static web server, from which the documents can be accessed via a client library or a regular web browser. A demo server is available at https://dtw.twinbase.org and new server instances can be initialized free-of-charge at GitHub via its browser interface. Twinbase is built with GitHub repository, Pages, and Actions but can be extended to support other providers or self-hosting. We describe the underlying architecture of Twinbase to support the creation of derivative and alternative server implementations. The Digital Twin Web requires permanent, globally accessible, and transferable identifiers to function properly, and to address this issue, we introduce the concept of digital twin identifier registry. Performance measurements showed that the median response times for fetching a digital twin document from Twinbase varied between 0.4 and 1.2 seconds depending on the identifier registry.