Michele Dominici

Belief Inference with Timed Evidence - Methodology and Application Using Sensors in a Smart Home.

Smart Homes need to sense their environment. Augmented appliances can help doing this but sensors are also required. Then, data fusion is used to combine the gathered information. The belief functions theory is adapted for the computation of small pieces of context such as the presence of people or their posture. In our application, we can assume that a lot of sensors are immobile. Also, physical properties of Smart Homes and people can induce belief for more time than the exact moment of measures.

Multi-sensor data fusion within the belief functions framework: application to smart home services

In Smart Home, understanding the environment and what is going on is the basis of all adapted services. Unfortunately, inferring situations and activity recognition directly from raw data is way too complex to be applied. Firstly, we present a layered architecture we are building to process raw data into abstract situations and activities. Secondly, data fusion tools using the belief functions theory are introduced as a general framework to provide a first level of abstraction from raw data given by sensors to a more complex context model. Then a methodology to apply the model to our Smart Home within the belief functions framework, a first implementation and the encountered issues in modeling are discussed.

Physical approach in smart homes: a proposition and a prototype

The state-of-the-art solutions in the Smart Home domain rely on a logical approach, based on a heavy instrumentation of the environment and on complex techniques that analyze very large amounts of data, collected by sensing devices disseminated in the environment. These aspects negatively influence the delivery of transparent and effective user services. This paper proposes the adoption of a physical approach, in which the information and the computations are carried and executed directly by augmented physical entities, allowing small, meaningful exchanges of data that need less complicated processing. The result is a seamless delivery of useful, transparent and effective user services. The paper describes this approach in detail, analyzes some drawbacks of the state-of-the-art Smart Homes, shows how the physical approach can address those issues and illustrates a prototype that demonstrates the feasibility of the proposed solution.

Experiences in managing uncertainty and ignorance in a lightly instrumented smart home

Purpose – The purpose of this paper is to report an inter‐disciplinary experience in building a context‐aware system that provides adapted functionalities to inhabitants of a smart home. The paper focuses on the management of uncertainty that is intrinsic to pervasive computing systems.Design/methodology/approach – The paper presents the principles that characterize the context‐aware architecture: the acceptability‐driven design, where privacy and acceptability are favored; the awareness of the gap between the reality of human activity and the capabilities of the capture process; the step‐by‐step abstraction of contextual information; the management of uncertainty imprecision and ignorance at individual‐ and cross‐layer levels. The paper presents the principles and describes the system architecture, focusing on the management of uncertainty.Findings – The authors built a layered architecture that manages and propagates uncertainty, imprecision and ignorance, allowing the recognition of ambiguous contexts ...

Towards a feasibility-driven uncertainty-aware layered architecture for recognizing complex domestic activity

This paper illustrates some recommended design principles for activity recognition techniques in the smart home domain. These include considerations about acceptability and feasibility and the adoption of realistic human activity models. The paper also presents the architecture of a smart home prototype that is currently under development. In this system, contextual information is obtained through successive abstractions. Mechanisms for assessing and propagating the uncertainty of the recognition process are also discussed.

Changing Interactions to Reduce Energy Consumption: Specification of a Context-Aware System Centered on the Home Occupants’ Concerns

This paper presents the specification of a context-aware system dedicated to assist home occupants in their everyday life while reducing their energy consumption. The system behavior and the interaction are built upon the definition of “situation spaces” based on a prior definition of the contexts of activity from the point of view of each actor in the home, i.e. taking into account actors’ concerns. The interaction specification appears to be a way to manage the discrepancy between users’ concerns and the system context, which can reduce errors. To develop context-aware systems that can easily be appropriated and thus potentially “invisible,” we believe it is essential to articulate choices about architecture and interaction with models of individual-collective activities built upon real-life observations.