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The construction of real-world knowledge is required if we are to understand real-world events that occur in a networked sensor environment. Since it is difficult to select suitable ‘events’ for recognition in a sensor environment a priori, we propose an incremental model for constructing real-world knowledge. Labeling is the central plank of the proposed model because the model simultaneously improves both the ontology of real-world events and the implementation of a sensor system based on a manually labeled event corpus. A labeling tool is developed in accordance with the model and is evaluated in a practical labeling experiment.

The object-blog service application automatically converts raw sensor data to environment-generated content (EGC), including texts, graphs, and figures. This conversion facilitates data searching and browsing. Generated content can serve several purposes, including memory aids, security, and communication media. In object-blog, personified objects automatically post entries to a Weblog about sensor data obtained from sensors attached to the objects. Feedback thus far from participants working with object-blog in an experimental environment has been positive.

We introduce a new data compression method for efficient data gathering in hierarchical sensor networks. Our proposed method compresses sensor data sequences by decomposing them into local patterns and weight variables using Singular Value Decomposition (SVD). Our proposed method can achieve efficient data gathering for environmental monitoring.

The new concept proposed in this paper is a query free web search that automatically retrieves a web page including information related to the daily activity that we are currently engaged in for automatically displaying the page on Internet-connected domestic appliances around us such as televisions. When we are washing a coffee maker, for example, a web page is retrieved that includes tips such as `cleaning a coffee maker with vinegar removes stains well.' A method designed on the basis of this concept automatically searches for a web page by using a query constructed from the use of ordinary household objects that is detected by sensors attached to the objects. An in-situ experiment tests a variety of IR techniques and the experiment confirmed that our daily activities can produce related web pages with high accuracy.

A sensor networked environment is capable of observing real-world phenomena as sensor readings, however, there are difficulties in understanding real-world ‘events’ such as activities of daily life occurring in the environment. We propose an incremental model for constructing real-world knowledge to allow us to understand real-world events. The central plank of the proposed model is the labeling practice. In the model, both the ontology of real-world events and the implementation of a sensor system are simultaneously improved based on a manually labeled event corpus. A labeling tool is developed in accordance with the model and event vocabularies are evaluated in a practical labeling experiment.

Motorbike racing is one of the most popular motorsports and many fans visit circuits to watch races. However, since audiences and pit crews can only obtain limited information, it is difficult for them to get detailed information about teams except for high ranking teams and few popular teams. To solve this problem, we have already presented an information browsing system for pit crews who used wearable computers. This paper describes an extension to the system. We also applied our system to racing audiences. Since our system can provide various information such as detailed ranking tables and favorite teams, it can make supporting the teams more advantageous and entertain audiences much more.

In this paper, we introduce our 's-room' project as well as the tagging strategies and environment developed for the project. In the s-room, many small sensor nodes are attached to various objects. Our project aims to construct a system for comprehending real-world events and the properties or status information of physical objects by utilizing sensor nodes distributed throughout the room as well as general knowledge obtained from web space. The events extracted in the s-room are then published as web contents. We defined a set of event descriptors as a middle language between the sensor data stream and natural language description. The descriptors are selected by a two-way method: 1) a top-down approach based on definitions in NL-dictionaries and laws in physics, 2) a bottom-up approach based on manually tagged sensor data streams. We also developed a tagging environment that enables us to arrange the relationship between NL phrase expressions of human activities and multiple sensor events automatically extracted from the sensor signal streams.

In the near future, small ubiquitous devices will be embedded into most of artifacts to support human dailylife. In such environments, we need multiple types of human-computer interfaces for enjoying ubiquitous services. This paper describes several ubiquitous gadgets; ubiquitous chip, Pin&Play, and VCC, to provide flexible ubiquitous services and user interfaces. The integrative use of these devices achieves the physical and intuitive interaction between users and ubiquitous services.

In this paper, we propose an application development environment for the ubiquitous chip, which is a rule-based event-driven input/output (I/O) control device for constructing ubiquitous computing environments. The proposed development environment simulates the behaviors of multiple ubiquitous chips and helps users to create rules. Moreover, it has a function for developing applications by cooperation between virtual ubiquitous chips and real ubiquitous chips. The application environment enables both programmers and general users to develop and customize applications for ubiquitous computing environments.

In this paper, we propose a new framework for ubiquitous computing by rule-based, event-driven I/O (input/output) control devices. Our approach is flexible and autonomous because it employs a behavior-description language based on ECA (Event, Condition, Action) rules with simple I/O control functions. We have implemented a prototype ubiquitous device with connectors and several sensors to show the effectiveness of our approach.