The use of context in mobile devices is receiving increasing attention in mobile and ubiquitous computing research. In this article we consider how to augment mobile devices with awareness of their environment and situation as context. Most work to date has been based on integration of generic sensor, in particular for positioning and for vision. We propose the integration of diverse simple sensors as alternative, aimed at awareness of situational context that can not be inferred from location, and targeted at resource constraint device platforms that typically do not permit processing of visual context. We have investigated multi-sensor contextawareness in a series of project and report experience from development of a number of device prototypes. These include development of an awareness module used for augmentation of a mobile phone, of the Mediacup exemplifying context-enabled everyday artefacts, and of the Smart-Its platform for aware mobile devices. The prototypes have been explored in a range of applications, to validate the multi-sensor approach to awareness, but moreover to develop new perspectives of how embedded context-awareness can be applied in mobile and ubiquitous computing.

Ubiquitous computing is giving rise to applications that interact very closely with activity in the real world, usually involving instrumentation of environments. In contrast, we propose Cooperative Artefacts that are able to cooperatively assess their situation in the world, without need for supporting infrastructure in the environment. The Cooperative Artefact concept is based on embedded domain knowledge, perceptual intelligence, and rule-based inference in movable artefacts. We demonstrate the concept with design and implementation of augmented chemical containers that are able to detect and alert potentially hazardous situations concerning their storage.

The imminent mass deployment of pervasive computing technologies such as sensor networks and RFID tags, together with the increasing participation of the Web community in feeding geo-located information within tools such as Google Earth, will soon make available an incredible amount of information about the physical and social worlds and their processes. This opens up the possibility of exploiting all such information for the provisioning of pervasive context-aware services for “browsing the world”, i.e., for facilitating users in gathering information about the world, interacting with it, and understanding it. However, for this to occur, proper models and infrastructures must be developed. In this paper we propose a simple model for the representation of contextual information, the design and implementation of a general infrastructure for browsing the world, as well as some exemplar services we have implemented over it. Keywords: Context-awareness, Location-dependent Services, Middleware, Sensor Networks, RFID Tags.

Context-aware computing is an emerging paradigm to free everyday users from manually configuring and instructing computer systems. As the general trend of computing is progressing towards an open and dynamic infrastructure, building context-aware systems can be difficult and costly. In order to build successful context-aware systems, we must develop an architecture to reduce the difficulty and cost of building these systems. This PhD. dissertation proposal describes a research plan to develop a broker-centric agent architecture that is aimed to relieve the burden of capability-limited agents of acquiring and reasoning about contexts, and to protect the privacy of users in a context-aware environment. The implementation of the Context Broker Archiecture will explore Web Ontology Language for modeling contexts and privacy policies, Jess for building a hybrid reasoning mechanism and JADE/FIPA for realizing broker behaviors and agent communications.

www.wearable.ethz.ch Abstract. The paper describes a method that allows us to derive the location of an acceleration sensor placed on the user’s body solely based on the sensor’s signal. The approach described here constitutes a first step in our work towards the use of sensors integrated in standard appliances and accessories carried by the user for complex context recognition. It is also motivated by the fact that device location is an important context (e.g. glasses being worn vs. glasses in a jacket pocket). Our method uses a (sensor) location and orientation invariant algorithm to identify time periods where the user is walking and then leverages the specific characteristics of walking motion to determine the location of the body-worn sensor. In the paper we outline the relevance of sensor location recognition for appliance based context awareness and then describe the details of the method. Finally, we present the results of an experimental study with six subjects and 90 walking sections spread over several hours indicating that reliable recognition is feasible. The results are in the low nineties for frame by frame recognition and reach 100 % for the more relevant event based case. 1

Services for mobile and pervasive computing should extensively exploit contextual information both to adapt to user needs and to enable autonomic behavior. This raises the problem of how to represent, organize, aggregate, and make available such data to services so as to have it become meaningful and usable knowledge. In this paper, we identify the key software engineering challenges introduced by the need of accessing and exploiting huge amount of heterogeneous contextual information. Following, we survey the relevant proposals in the area of context-aware pervasive computing, data mining and granular computing discussing their potentials and limitations with regard to their adoption in the development of context-aware pervasive services. On these bases, we propose the W4 model for contextual data and show how it can represent a simple yet effective model to enable flexible general-purpose management of contextual knowledge by pervasive services. A summarizing discussion and the identification of current limitations and open research directions conclude the paper.

This paper presents a survey of sensors for the use in networked embedded sensing devices. The most typical sensors needed for applications in Ubiquitous and Pervasive Computing are identified through a survey of 12 typical existing and implemented applications using over 300 wireless sensor nodes. In total, about 45 different types of objects with embedded networked sensor nodes build the basis for the analysis. We identified 7 general types of sensors - namely movement, light, force, temperature, audio, humidity and proximity - that are commonly used in all these settings and subsequently listed typical context information that can be derived from them. Based on the analysis the paper also introduces an exemplary platform, the Particle Sensor Board, where such sensors are implemented and presents an overview of their characteristics.

Ambient intelligent applications require applications to recognise user activity calmly in the background, typically by instrumentation of environments. In contrast, we propose the concept of Cooperative Artefacts (CAs) to instrument single artefacts that cooperate with each other to acquire knowledge about their situation in the world. CAs do not rely on external infrastructure as they implement their architectural components, i.e. perceptual intelligence, domain knowledge and a rule-based inference engine, on embedded devices. We describe the design and implementation of the CA concept on an embedded systems platform and present a case study that demonstrates the potential of the CA approach for activity recognition. In the case study we track surface-based activity of users by augmenting a table and household goods.

In this paper, we introduce a new paradigm for global computation, one in which the context of collected information drives the type of processing and dissemination the information receives as it is dispersed around the world. The creation of this model has necessitated the development of new types of methods for securing contextual information because the internet itself inherently has not have security mechanisms. Security is typically localized at the nodes on the internet that process information. There are multiple models and methods that are under development to provide security for contexts. This paper presents the basics of a model that allows context consumers to determine the level of security contextual information should have. Security levels have a direct correlation with confidence in the integrity of contextual data and thus application of its processing. Keywords global contextual processing, contextual processing security, security brane. 1.

Abstract. Ambient Intelligence (AmI) refers to an environment that is sensitive, responsive, interconnected, contextualized, transparent, intelligent, and acting on behalf of humans. This environment is coupled with ubiquity of computing devices that enables it to transparently sense context changes, to react accordingly, and even to take the initiative towards fulfilling human needs. Security, privacy, and trust challenges are amplified with AmI computing model and need to be carefully engineered. From software engineering perspective, the shift towards AmI can be seen abstractly similar to the shift from object paradigm towards agent one. Objects provide functionality to be exploited, while agents possess functionality and know how and when to use and offer it autonomously. Agent paradigm is suitable for implementing AmI considering AmI as an open complex system. Moreover, we argue that agent paradigm is equally useful for engineering all aspects of such systems from the early phases of software development life cycle. 1