Urban environments can be challenging to navigate due to the often ambiguous, sometimes even repetitive cues, combined with the cognitive pressure of busy surroundings. The last step of navigation, reaching the goal, may still be frustrating for an unfamiliar target. We pursue a visualization for instantaneous identification of a proximal but ambiguous target, freeing us from turn-by-turn guidance. We present a field experiment for bus stop spotting in a central public transport hub using a 2D map, augmented reality (AR), and realistic 3D maps at oblique bird’s eye view and at ground level. 3D Bird’s eye view provided fastest responses and highest success rates. AR and 2D map provided slowest responses and lowest success rates. 3D ground level view performed between these, but without a significant difference to AR and 2D map. 3D Bird’s Eye view was considered the most useful modality by subjects, and was also selected as the preferred modality.

This paper introduces a design framework for mixed reality urban exploration (MRUE), based on a concrete implementation in a historical city. The framework integrates different modalities, such as virtual reality (VR), augmented reality (AR), and haptics-audio interfaces, as well as advanced features such as personalized recommendations, social exploration, and itinerary management. It permits to address a number of concerns regarding information overload, safety, and quality of the experience, which are not sufficiently tackled in traditional non-integrated approaches. This study presents an integrated mobile platform built on top of this framework and reflects on the lessons learned.

The Internet of Things (IoT) has led towards a digital world in which everything becomes connected. Unfortunately, most of the currently marketed connected devices feed vertically-oriented closed systems (commonly referred to as vertical silos) which prevent the development of a unified global IoT. This issue is all the more valid in complex environments, such as smart cities, in which exceedingly large amounts of heterogeneous sensor data are collected, and in which platforms and stakeholders should also be able to interact and cooperate. Therefore, it is of utmost importance to move towards the creation of open IoT ecosystems to support efficient smart city service integration, discovery and composition. This paper contributes to the specifications of such an ecosystem, which has been developed as part of the EU's H2020 bIoTope project. The novelty of this ecosystem compared with the current literature is threefold: (i) it is based on the extensive use of open communication and data standards, notably O-MI and O-DF standards, that foster technical, syntactic and semantic interoperability over domains; (ii) it proposes an innovative service marketplace for data/service publication, discovery and incentivization; (iii) it integrates security functionalities at the IoT gateway level. The practicability of our ecosystem has been validated through several smart city proofs-of-concept set up in three distinct cities: Helsinki, Lyon and Brussels. Given the five major themes defined in the CITYKeys (a smart city performance indicator framework), namely People, Planet, Prosperity, Governance and Propagation, bIoTope mainly contributes to Prosperity-related metrics, as discussed in this paper.

Many hobbies and household activities can be carried out with little effort, and without deeper understanding of the phenomenon at hand. Managing houseplants and herbs is such a hobby; one can simply provide water for plants and hope they would prosper. However, some people seem to have a better luck in maintaining their plants, while many fail and claim they do not possess a “green thumb”. Fortunately, this does not require magic, but engineering. We use innovative Internet of Things and artificial intelligence technologies to monitor and analyze moisture, humidity, luminosity and temperature levels to assist end users for optimization of environmental conditions for their houseplants, simultaneously increasing their understanding of plant life. For plant health monitoring, we construct a system yielding the normalized difference vegetation index, supported by visual validation by users. We run the system for a selected plant, basil, in varying environmental conditions to cater for typical home conditions in pursue of bootstrapping our artificial intelligence with the acquired data. For end users, we implement a web based user interface which provides both instructions and explanations.

Air pollution is a severe health issue. In urban environments, traffic is the main pollution source. Pollution disperses from main roads to the environment depending on weather conditions and city structure. Given dense air quality data, one could create routes that optimize journeys to avoid polluted air. We provide a methodology for this, and have implemented a Clean Air Journey Planner for the City of Helsinki. We have done this by modifying the existing Open Source journey planner (the Digitransit platform), extended by integrating high resolution (13m grid size) air quality data generated hourly with the ENFUSER dissipation model by the Finnish Meteorological Institute. The Planner is suited for pedestrians and allows citizens to find routes with less pollution. It is the first to utilize near real time updated high resolution air quality data directly in the routing core of a widely used Open Source journey planner.

The built environment provides significant opportunities for IoT (Internet of Things) deployment, and can be singled out as one of the most important aspects for IoT related research. While the IoT deployment in the built environment is growing exponentially, there exists a gap in integrating these two in a systematic way through open standards and systems. From technological perspective, there is a need for convergence of diverse fields ranging from Building Information Systems and Building Services to Building Automation Systems, and IoT devices and finally the end user services to develop smart, user oriented applications. This paper outlines the efforts to develop a platform that integrates the built environment data with IoT sensors in a campus wide, web based system called Otaniemi3D that provides information about energy usage, occupancy and user comfort by integrating Building Information Models and IoT devices through open messaging standards (0-MI and 0-DF) and IFC models. The paper describes the design criteria, the system architecture, the workflow and a proof of concept with potential use cases that integrate IoT with the built environment. Initial results show that both the end users and other research groups can benefit from such platforms by either consuming the data in their daily life or using the data for more advance research.

Many domains are trying to integrate with the Internet of Things (IoT) ecosystem, such as public administrations starting smart city initiatives all over the world. Cities are becoming smart in many ways: smart mobility, smart buildings, smart environment and so on. However, the problem of non-interoperability in the IoT hinders the seamless communication between all kinds of IoT devices. Different domain specific IoT applications use different interoperability standards. These standards are usually not interoperable with each other. IoT applications and ecosystems therefore tend to use a vertical communication model that does not allow data sharing horizontally across different IoT ecosystems. In 2014, The Open Group published two domain-independent IoT messaging standards, O-MI and O-DF, aiming to solve the interoperability problem. In this article we describe the practical use of O-MI/O-DF standards for reaching interoperability in a mobile application for the smart city context, in particular for the Smart Mobility domain, electric vehicle (EV) charging case study. The proof-of-concept of the smart EV charging ecosystem with mobile application user interface was developed as a part of an EU (Horizon 2020) Project bIoTope.

The next generation of social media will utilize advanced visualization methods for real time co-experiencing of real environments. Our cases promote the use of virtual and augmented reality, visualizing people, vehicles and content on mobile devices and immersively with head mounted displays on desktops. Our demonstrations include Android tablets and Oculus Rift/HTC VIVE displays.

Human sensory system is a complex mechanism, providing us with a wealth of data from our environment. Our nervous system constantly updates our awareness of the environment based on this multisensory input. We are attuned to cues, which may alert of a danger, or invite for closer inspection. We present the first integrated mobile platform with state-of-the-art visual, aural and haptic augmentation interfaces, supporting localization and directionality where applicable. With these interfaces, we convey cues to our users in the context of urban cultural experiences. We discuss the orchestration of such multimodal outputs and provide indicative guidelines based on our work.

In public transportation, quality of service is of paramount importance. In a study on public transportation reliability, approximately half of the riders reduced their use of services due to unreliability, switching to other modes of transportation [Carrel et al. 2013]. It is also known that the perceived wait time at a bus stop is greater than the actual wait time and a real time information diminishes this difference [Mishalani et al. 2006]. However, when real time data itself is unreliable, this is felt particularly frustrating [Carrel et al. 2013].

We present an interaction technique that integrates spatial sensing to an interactive 3D city model in order to support efficient localization of objects (esp. buildings) known or remembered in the real world. The technique offers a unified 3D interaction scheme for both visible and remote objects. In the egocentric view, sensor data from the mobile device (accelometer, gyroscope, GPS) is utilized to couple the viewport to user's movement similarly as in mobile AR. The technique offers easy shifting from the viewport-coupled mode to a top-down view where movement is POI-based. A field experiment compared it to an exocentric technique resembling the traditional pan-and-zoom in 2D mobile maps. The two techniques showed differential benefits for target acquisition performance.

We present the first study to discover optimal reality sampling for mobile imagery. In particular, we identify the minimum information required for fast recognition of images of directly perceivable real-world buildings displayed on a mobile device. Resolution, image size, and JPEG compression of images of façades were manipulated in a same--different recognition task carried out in the field. Best-effort performance is shown to be reachable with significantly lower detail granularity than previously thought. For best user performance, we recommend presenting images as large as possible on the screen and decreasing resolution accordingly.

Recently, mobile-phone based outdoor augmented reality (AR) systems have become readily available. One of the most popular applications are AR browsers that show virtual points of interest (POIs) overlaid on top of the phone's camera view. These virtual cues can be used to guide people to the POIs. However, the usefulness of AR systems for guiding users to POI has not yet been evaluated, especially when compared to map interfaces. In this paper we present results of a user study comparing navigation with information typically provided by currently available handheld AR browsers, to navigation with a digital map, and a combined map and AR condition. We found no overall difference in task completion time, but found evidence that AR browsers are less useful for navigation in some environment conditions. We also found that navigation performance differed significantly with gender for the Map and AR+Map interfaces, but is very similar across gender for the AR interface. Users preferred the combined AR+Map condition, and felt that there were significant problems with using the AR view alone for navigation.

Modern mobile devices can act as advanced graphical interfaces to our environment. Mobile augmented reality (AR) systems provide a direct egocentric view, where content is overlaid on top of a camera feed. This user interface is intuitive, as it is based on the simple pointing paradigm. It suits 'what is?' pull-type tasks for visible content. For occluded content, further issues arise, both for target selection (for known targets) and for inferring the actual physical position (for unknown targets). For navigation use, AR does not allow spatial browsing or route planning -- it does not convey configurational knowledge of the environment, which is what abstract 2D maps are designed for. Indeed, these two views are rather different, and pose a mental jump in representation. We hypothesize that a realistic 3D model can act as a transitional mode between a fully realistic AR and an abstract 2D map, or could replace either or both of them altogether for most spatial tasks.

Modern mobile devices and networks facilitate the development of increasingly graphical and complex mobile GIS or geomedia applications. We advance the state-of-the-art with the HYDROSYS system, a heterogeneous platform integrating multiple data sources and components, allowing interactive environmental data analysis and monitoring in the field. Our key contributions are 1) scalable on-the-fly streaming of environmental sensor data, 2) highly graphical mixed reality representations embedding multivariate sensor data visualizations, including access to results of near real time simulations and other physically-based computations, 3) support for semantically meaningful public participation. We balance the use of standardized formats and optimized mobile transmissions. Our system builds on use cases ranging from hydrological professionals and municipal authorities to the environmentally-aware public. We present the challenges, solutions and implementation of the system, providing observations on potential bottlenecks.

How to experience real-world landmarks through a wave, gaze, location coordinates, or touch, prompting delivery of useful digital information.

This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Helsinki University of Technology's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org.