Smart Office Environment Research Articles

Agent system using multimodal interfaces for a smart office environment

This paper presents an experimental study on an agent system with multimodal interfaces for a smart office environment. The agent system is based upon multimodal interfaces such as recognition modules for both speech and pen-mouse gesture, and identification modules for both face and fingerprint. For essential modules, speech recognition and synthesis were basically used for a virtual interaction between user and system. In this study, a real-time speech recognizer based on a Hidden Markov Network (HM-Net) was incorporated into the proposed system. In addition, identification techniques based on both face and fingerprint were adopted to provide a specific user with the service of a user-customized interaction with security in an office environment. In evaluation, results showed that the proposed system was easy to use and would prove useful in a smart office environment, even though the performance of the speech recognizer was not satisfactory mainly due to noisy environments.

Services and Applications for Smart Office Environments - A Survey of State-of-the-Art Usage Scenarios

This paper reports on a survey of state-of-the-art application scenarios for smart office environments. Based on an analysis of ongoing research activities and industry projects, functionalities and services of future office systems are extracted. In a second step, these results are used to identify the key characteristics of emerging products.

Data Mining for Hierarchical Model Creation

In this paper, we examine the problem of learning inhabitant behavioral models in intelligent environments. We maintain that inhabitant interactions in smart environments can be automated using a data-driven approach to generate hierarchical inhabitant models and learn decision policies. To validate this hypothesis, we have designed the ProPHeT decision-learning algorithm that learns a strategy for controlling a smart environment based on sensor observation, power line control, and the generated hierarchical model. The performance of the algorithm is evaluated using real data collected from our MavHome smart home and smart office environments.

The reflective mobile agent paradigm implemented in a smart office environment

Ubiquitous systems will integrate computers invisibly and unobtrusively in everyday objects. Data will be catched from single or multi-sensor devices and will be used for context extraction. New location-based services will be adapted to user preferences. For this the ubiquitous system needs to know user profiles, likings, and habits. As the user moves, these information must be made available at the new location of the user. Either the user carries the data on wearable or portable computers or the smart environment takes responsibility for transporting them. The amount of new devices and services makes an efficient use by centralized systems very difficult. The idea presented in this paper is that a virtual reflection of the user represented by a mobile agent accompanying in the smart environment. Mobile agents offer a possibility to encapsulate information of a person and the person’s preferences and perform location-based services of the ubiquitous system in the name of the user. Security and privacy are major concerns of such an agent system. This paper describes a ubiquitous mobile agent system named UbiMAS which has security extensions to provide high protection of agents and significant personal data. UbiMAS is applied in the smart doorplate project as part of a smart office environment.

Interactive performance environments and the visualisation of actor movement

The recent production of Eugene Ionesco's Macbett at the UCLA Department of Theater was the department's first performance to incorporate 'interactive systems' that allowed lighting and sound to adapt automatically to performer position and movement. Sensing and response technology on the stage is introduced here as a precursor to the smart home and office environments imagined by proponents of 'ubiquitous computing'. This paper presents early two-dimensional visualisations of the performer tracking data and discusses their influence on systems development. A few possible extensions to the visualisation techniques given here are also discussed.

An authorization-based trust model for multiagent systems

In this paper an authorization-based trust model (ABTM) is described which is designed for managing access to services in a semi-open distributed environment. This is called a multiagent-based smart office environment. In this model, "trust" is defined as a set of authorization attributes that are granted by the owner of a service to the user of the service. Central to this model is a trust manager that redelegates authorizations from the service owner to the requesting user, based on access control policies that are specified by role labels which are assigned to a set of agents. The ABTM scheme is different from a centralized scheme, in which authorizations are granted directly by an authority. It is also different from a fully distributed system,where authorizations are granted based solely on the discretion of the owner of the services. The design philosophy is the separation of trust management and trust application to allow efficient management of access control in large-scale and dynamic environment, such as those that exist in multiagent systems.

Smart office robot collaboration based on multi-agent programming

As a new Artificial Intelligence (AI) application to our everyday life, we designed and implemented a smart office environment in which various information appliances work collaboratively to support our office activities. In this environment, many cameras and infrared sensors allow handling robots and mobile robots to perform complex tasks such as printing and delivering document. The delivery task is a typical example of an important class of tasks supporting humans in the smart office. In this paper, such robots are modeled as robotic agents, and collaboration between the agents is realized using multi-agent programming. We have developed a multi-agent robot language (MRL) as an evolution of concurrent logic programming. MRL provides synchronous and asynchronous control of agents based on guarded Horn clauses. It also supports describing an advanced negotiation protocol using broadcast and incomplete messages, and making decisions using a set of logical rules. These features are unified within an MRL framework, yielding an intelligent integration of the robotic agents. We view the smart office environment as a human assistant system through agent collaboration, and this view is novel and extendable as AI for everyday functions.