AMBIENT INTELLIGENTJosé Manuel Molina López

Catedrático de Ciencia de la Computación e Inteligencia Artificial

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DefinitionUbiquitous ComputingContext

Ambient Intelligence

Ambient Intelligence

Ambient Intelligence (AmI) envisions a future Information Society where users are proactively, but sensibly provided with services that support their activities in everyday life

AmI scenarios described by the European Commission Information Society Technologies Advisory Group (ISTAG) depict intelligent environments capable of recognising and responding to the presence of different individuals in a seamless, unobtrusive and often invisible way

AmI is strongly founded on the concept of Ubiquitous Computing (UC), introduced by Weiser in the early 90s, which presents a world where a multitude of computational objects communicate and interact in order to help humans in daily activities.

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Ubiquitous

Computing

Ubiquitous Computing

“Ubiquitous computing has as its goal the enhancing computer use by making many computers available

throughout the physical environment, but making them effectively invisible to the user”. [Weiser, 1993]

The main objective for AmI systems is to be invisible but helpful.

Requirements technology must be transparent to users services must be tailored to user context and preferences applications must be interoperable and easy to interact

with.

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What’s CONTEXT

Context5

Dey defines context as any information that can be used to characterize the situation of an entity. An entity is a person, place, or object that is considered relevant to the interaction between a user and an application, including the user and applications themselves

[Anind K. Dey and Gregory D. Abowd. Towards a Better Understanding of context and context-awareness. Technical Report GIT-GVU-99-22, Georgia Institute of Technology, College of Computing, June 1999.]

Schmidt et al. define context as knowledge about the users and IT devices state, including surroundings, situation, and to a less extent, location.

[Albrecht Schmidt, Kofi Asante Aidoo, Antti Takaluoma, Urpo Tuomela, Kristof Van Laerhoven, and Walter Van de Velde. Advanced interaction in context. In Proceedings of First International Symposium on Handheld and Ubiquitous Computing,HUC'99, pages 89-101, Karlsruhe, Germany,September 1999. Springer Verlag].

Context6

Schilit divides context into three categories:

Computing context, such as network connectivity, communication costs, and communication bandwidth, and nearby resources such as printers, displays, and workstations.

User context, such as the users profile, location, people nearby, even the current social situation.

Physical context, such as lighting, noise levels, traffic conditions, and temperature.

[Bill Schilit, Norman Adams, and Roy Want.Context-aware computing applications. In Proceedings of IEEE Workshop on Mobile Computing

Systems and Applications, pages 85-90, Santa Cruz, California, December 1994. IEEE Computer Society Press]

Context7

Important notes about context by Schilit:

– Who ( Identity Awareness).- It’s the way the context distinguish the user profile to achieve the correct behavior.

– What ( Task Awareness).- It concentrates what the user is doing, the task he is managing and what he want to obtain. It has to do with the services offered by the system.

– Where ( Location Awareness).- Knowledge of the physic location,

– When ( Time Awareness).- Acquisition and maintenance of the information about time and date, static schedules and dynamism of each user’s diary.

– Why (Device behavior).- To easily communicate with the computer in order to manage everyday tasks, as far as possible, in an implicit way.

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Communication TechnologiesInformation ProcessingService-Providing FrameworkApplications

Research Areas

Communication Technologies9

Distributed devices to gather and provide information need networking functionalities.

ad hoc technologies: RFID (active tags) Bluetooth Zigbee (short-range) Wi-Fi or WiMax (medium-range)

Broadband cell phone technologies (4G) NOW common infrastructures based on IP protocols,

Internet of Things (IoT). The IoT, based on the next-generation IPv6, is emerging to

be the communication support of AmI, which requires the participation of heterogeneous devices and transport technologies.

Information Processing10

Fusion Technologies Extract, contextualize and represent information Areas:

Knowledge Mobilization Data Mining Information Fusion Machine Learning

Ontologies to represent and reason with heterogeneous information.

Service-Providing Framework11

Distribution of knowledge, which is essential in AmI, can be accomplished with technologies such as MAS, Web Services and Cloud Computing.

The Multiagent Systems (MAS) paradigm proposes a scenario where independent, goal-directed, and environment-aware units (the agents) get coordinated (by collaborating or competing) to accomplish complex tasks.

Web Services allow remote procedures to be requested through elaborated HTTP calls, including procedures for service choreography (which messages are created when the service is requested) and orchestration (which external services are required to complete the task).

Cloud Computing is a recent service-providing model oriented to guarantee system scalability. Users access to remote computing resources on demand without regard of the situation of the resource and the communication technology.

Applications12

Friendly interfaces to final users: Human-Computer Interaction

Deployment of infraestructure Areas:

e-Health Ambient Assisted Living Surveillance applications Intelligent avoiding of collisions Hazardous drug control Food traceability Logistics .. etc.

Research Areas in Ambient Intelligence13

1. SupportingTechnologies

HCI

2. InformationProcessing

Internet of Things

Middleware Abstraction Layer

DevicesCommunication

Wi-Fi Bluetooth RFID UWB Zigbee 3.5G/4GSensors Tags Video cameras

Soft Computing Methodologies

KnowledgeMobilization Data Mining Information

FusionMachine Learning

Ontologies Semantic Web Fuzzy Logic Intelligent Databases Data Warehouse Multimedia

Information Integration Scene Recognition Context-Awareness User Profiling

Distributed Knowledge Management

Intelligent Service-Providing Framework

MAS WebServices

CloudComputing

HealthcareDisabled people

Elder careAccident

prevention

Monitoring

Logistics Intelligent Infrastructure

SecuritySurveillance

Intrusion detection

Threat reaction

3. Service-Provision Framework

4. Applications

Services

Knowledge

Information

Data

Users

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Non-Intrusive IdentificationEvaluationMobile sensors

Open Problems

Non-Intrusive Identification15

• Face Recognition But now people is walking

• And we want context

Evaluation16

Mobile Sensors17