A Quantitative Analysis of Power Consumption for Location-Aware Applications on Smart Phones
The industry is producing new wireless mobile devices, such as smart phones, at an ever increasing pace. In terms of processors and memory, these devices are as powerful as the PCs were one decade ago. Therefore, they are perfectly suitable to become the first real-life platforms for ubiquitous computing. For instance, they can be programmed to run location-aware applications that provide people with real-time information relevant to their current places. Deploying such applications in our daily life, however, requires a good understanding of their power requirements in order to ensure that mobile devices can indeed support them. This paper presents a quantitative analysis of power consumption for location-aware applications in our SmartCampus project, which builds a large scale test-bed for mobile social computing. Based on this analysis, we conclude that carefully designed applications can run for up to six hours, while updating the user location frequently enough to support real-time location-aware communication.
Computer Science, Engineering
Some Lessons for Location-aware Applications
This paper talks about user needs rather than the details of interfaces. It covers certain kinds of location-aware applications, plus context-aware applications in general. It is a shortened version of the paper found at Paper given at Glasgow workshop References 1. http://www.cs.ukc.ac.uk/people/staff/pjb/papers/glasgowworkshop.html
Computer Science, Economics
A Middleware Architecture for Dynamic Reconfiguration of Agent Collaboration Spaces in Indoor Location-Aware Applications
Recently, indoor location-aware applications that provide interactive capability with the surrounding physical environment are increasingly in demand. These applications include mobile asset management, indoor navigation, and location-based reservation systems. In many cases, these services require multiple and dynamic collaborations over a large number of service subscribers with a deterministic, fast response time. However, many studies still function primarily on client/server-based centralized architectures that are inefficient in supporting complex collaboration, due to their static organization and unpredictable network congestion. To address this problem, we propose a middleware architecture named Dynamic Reconfigurable Agent Space (DRAS), based on a collaboration of service agents that can be distributed over the requested service area. A service application can dynamically modify a service area according to the request of the service subscribers under the DRAS. To demonstrate the feasibility and performance of the DRAS, we evaluated the elapsed time for dynamic reconfiguration of the service area. Also, two general collaboration scenarios in indoor location-aware applications called voting and tracking were evaluated in the simulation and in a real environment. The evaluation shows that the proposed middleware is suitable for indoor location-aware applications that require a large number of mobile nodes and complex collaboration by the effective distribution of network traffic and processing around the service agents.
Augmented reality in support of interaction for location-aware applications
There has been an increased interest in both the augmented reality (AR) and ubiquitous computing (Ubicomp) research communities to integrate these two technologies. In an attempt to introduce visual interaction into location-aware applications we have developed a prototype that lets users experience a Ubicomp environment visually. Some system issues we came across in accomplishing this task are described.
Inverting Systems of Embedded Sensors for Position Verification in Location-Aware Applications
Wireless sensor networks are typically deployed to monitor phenomena that vary over the spatial region the sensor network covers. The sensor readings may also be dual-used for additional purposes. In this paper, we propose to use the inherent spatial variability in physical phenomena, such as temperature or ambient acoustic energy, to support localization and position verification. We first present the problem of localization using general spatial information fields, and then, propose a theory for exploiting this spatial variability for localization. Our Spatial Correlation Weighting Mechanism (SCWM) uses spatial correlation across different phenomena to isolate an appropriate subset of environmental parameters for better location accuracy. We then develop an array of algorithms employing environmental parameters using a two-level approach: first, we develop the strategies on how the subset of parameters should be chosen, and second, we derive mapping functions for position estimation. Our algorithms support our theoretical model for performing localization utilizing environmental properties. Finally, we provide an experimental evaluation of our approach by using a collection of physical phenomena measured across 100 locations inside a building. Our results provide strong evidence of the viability of using general sensor readings for location-aware applications.
Towards an MQTT5 geo-location extension for location-aware applications
Location-aware applications are becoming popular nowadays because of the increasing adoption of edge and fog computing. This poses novel difficulties to the conventional applications that utilize the Message Queuing Telemetry Transport (MQTT) as their prevalent communication channel. Also, developers are obliged to figure out the code at whatever point they need to build up MQTT-based location-aware applications. This can causes various issues, for example, protocol standard infringement or problems in data acquisition. This paper proposes a novel extension of the recently released MQTT5 protocol that will permit message delivery by not only respecting the topics of interest but also in addition to geo-referenced information provided by both publishers and subscribers.
The aWearable Toolkit: Supporting End-User Customization of Embodied Location-Aware Applications
We live in a mobile society where we are constantly surrounded by technology. Users are becoming technologists and many have been introduced to programming at some level. Previous work in HCI has been based on involving end-users in the design process. Now there is also focus on end-user development, which allows end-users to develop and customize systems. Embodied Social Interaction is another field that is getting attention these days. The main idea is to move computing out of the desktop and into physical objects. It integrates technology into everyday environments, and incorporates human?s un- derstandings of the physical and social world. Embodied social interaction is closely related to location-aware computing. Technology has become mobile and there is a need to keep track of where it has gone. By embodying location-awareness, we can free the hands of users and present information in the periphery of a person?s attention, limiting distraction. This master thesis combines end-user development and embodied location-awareness. We wish to provide users with tools to tailor applications to fit their needs. The main research question concerns how to support end-user customization of embod- ied location-awareness applications. As a result we have developed a prototype, the aWearable toolkit for end-users. We started out with an exploratory study of embodied social interaction, which was continued with a research study of embodied location-aware applications and end- user toolkits. Results of the research studies were used to define a set of scenarios that helped us identify requirements. After implementing the toolkit we conducted user evaluations where we looked at how well users were able to customize and use an application. These user-evaluations, along with the research studies, helped us answer the research questions.
Computer Science, Engineering