Corina Kim Schindhelm

Enabling IoT Ecosystems through Platform Interoperability

Today, the Internet of Things (IoT) comprises vertically oriented platforms for things. Developers who want to use them need to negotiate access individually and adapt to the platform-specific API and information models. Having to perform these actions for each platform often outweighs the possible gains from adapting applications to multiple platforms. This fragmentation of the IoT and the missing interoperability result in high entry barriers for developers and prevent the emergence of broadly accepted IoT ecosystems. The BIG IoT (Bridging the Interoperability Gap of the IoT) project aims to ignite an IoT ecosystem as part of the European Platforms Initiative. As part of the project, researchers have devised an IoT ecosystem architecture. It employs five interoperability patterns that enable cross-platform interoperability and can help establish successful IoT ecosystems.

Activity recognition and step detection with smartphones: Towards terminal based indoor positioning system

For years now, many indoor positioning techniques have been researched and some approaches have even been developed into consumer products. Solutions range from using existing WiFi structures to higher accuracy proprietary solutions, e.g. products using UWB (Ultra Wide Band). When public institutions such as libraries or shopping malls offer applications for users (e.g. shop finders), a problem of user privacy can arise. That is, depending on the type of positioning topology implemented, the user and his habits might become traceable. Since modern devices are increasingly equipped with better sensors, they could be used for independent terminal based positioning systems based on step detection. Hence, we decided to explore the capabilities of using the sensors of the HTC hero smartphone for detection of steps and of the movement/activity type. We implemented and examined three state of the art algorithms for these types of detection. The experimental results of detecting activities, e.g. “walking” and “jogging,” will be presented along with the different influencing factors such as types of shoes and position of the device. For future work we are working on an automatic and autonomous step length calculation system in order to come one step closer to a real terminal based positioning system.

Usability of apple iPhones for inertial navigation systems

In recent decades, many indoor positioning techniques have been researched and some approaches have even been developed into consumer products. Most of them have been deployed into companies which benefit from indoor asset tracking. However, for public buildings like libraries or transportation systems, no direct benefit exists by installing expensive systems. Inertial navigation systems offer a form of positioning which is almost completely independent from external infrastructures, inexpensive and privacy friendly. As prices for sensors continuously drop, mobile terminals, such as cell phones or tablet PCs, are being equipped with various additional components, like GPS, cameras and light sensors, and moreover gyroscopes, compasses and accelerometers integration is also becoming commonplace. These last three components enable inertial navigation systems to calculate the position of the device. In this paper, we selected two devices, the iPhone 3GS and the iPhone 4, to analyze their sensors for usability of an inertial navigation system. For each device a common strapdown algorithm was implemented and varying standard filters applied to clean the output data stream of the sensors. Finally, we present the results, which are diverse according to the devices.

Overview of Indoor Positioning Technologies for Context Aware AAL Applications

Many AAL scenarios, such as those found in the public-funded German R&D project SmartSenior, are based on location information about a person, which makes the position key context information. Previous papers have dealt with the design of a SmartSenior positioning system for emergency scenarios, both indoors and outdoors. This paper focuses on non-critical non-emergency scenarios, e.g., activity recognition and indoor navigation. We present the state-of-the-art in indoor positioning and the current research trend towards including additional sensor information to achieve positioning enhancements and gather more context information. After introducing a few interesting scenarios, we present a guideline on how indoor positioning can be classified in technical ways and also in more abstract ways. We also define metrics (accuracy, costs, privacy, context information) which we then use to evaluate the current state-of-the-art research. Based on this evaluation, we discuss possible solutions for the previously presented scenarios.

Distributed Cooperative On-Demand Transportation

In current transport logistics, routing is usually performed centrally. This paper presents a novel approach introducing dynamic transfer nodes and a distributed decision process to redeploy transport objects. Thus, transportation vehicles, such as buses, operate autonomously and communicate among each other to optimise the redistribution of their current passengers. Because the system works without a central component it can easily be extended to fit specific transportation scenarios or the passenger penetration rate. The feasibility of this approach is evaluated utilizing a simulator which considers important aspects, including transfer times, passenger waiting and drive time, covered distance, etc. The experiments show promising results. On average the drive time for a passenger could be decreased by up to 10% and waiting times by more than 20%. In addition, the total covered distance is reduced compared to an approach where no transfer nodes are used.

Community based approach for generating building layouts

In this paper we propose the design and evaluation of an algorithm capable of inferring basic floor plans from motion paths generated from smartphone sensors. First we shortly discuss the applicability of modern smartphones equipped with various sensors to create motion paths through premises. Some dead reckoning approaches which are used to track and calculate the position of devices are mentioned. After that we present an algorithm which shall use motion paths for the creation of maps holding probabilistic information regarding the accessibility of specific areas within a confined structure such as a building. The algorithm thus differs from traditional SLAM and mapping approaches in that it explicitly focuses on map generation and path interpretation and does not implement any sort of sensor-specific processing. In the concluding evaluation it is shown that the presented algorithm while still prone to certain types of bad input data can calculate free space from the motion paths with a sufficient accuracy for basic mapping tasks, especially if more input samples are used. Finally, various possible improvements are discussed which may improve the algorithms processing quality and robustness.