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The disinfection of environmental surfaces is an effective countermeasure for COVID-19. In this paper, we use a thermographic camera and lightweight background image processing and propose a method that detects and visualizes the places touched by a person. Our method will support effective disinfection activities.

Agile environmental monitoring is a novel style of environmental-monitoring development that lets you rapidly develop sensor devices and monitoring systems through trial and error during continuous sensing. The authors developed three environmental-monitoring systems and adapted them in situ based on actual field requirements. This article is part of a special issue on smart cities.

In this paper, we propose PASNIC, a lightweight privacy-aware sensor node for image capturing. PASNIC masks the region of faces and private screens (smartphone and portable computer displays) in captured visible images before sending them to remote sites. Thermal information, which can also be captured with a thermal image sensor, is used to detect the regions of faces and private screens. Our masking algorithms are so simple that even sensor nodes with low processing power can sufficiently process them.

For protecting the public health, many research groups have tried to capture dense air quality information using sensorized vehicles that travel within urban areas. However, it remains difficult to accumulate real-time and fine-grained air quality information to fulfill a wide variety of requests from citizens and authorities. In this paper, we propose on-demand urban air quality monitoring using public vehicles. By adapting the monitoring behavior of sensors to each city's individual's needs, smart cities can accumulate enough air quality information with just a few sensorized vehicles. This paper describes the mechanisms of remote update programs on sensor nodes mounted on public vehicles for on-demand monitoring. We adopted the mechanisms on sensorized public vehicles in Fujisawa City, Japan. The paper also reports our air quality monitoring field trial and describes a functional design for on-demand air quality monitoring.

Activity recognition is a key technology for realizing ambient assisted living applications such as care of the elderly and home automation. This paper proposes a new activity recognition method that employs hand-worn magnetic sensors to recognize a broad range of activities ranging from simple activities that involve hand movements such as walking and running to the use of portable electrical devices such as cell phones and cameras. We sense magnetic fields emitted by electrical devices and the earth with hand-worn sensors, and recognize what a user is doing or which electrical device the user is employing. We frequently use a large number of different electrical devices in our daily lives, and so we can estimate high-level daily activities by recognizing their use. Our approach permits us to recognize a range extending from low-level simple activities to high-level activities that relate to the hands without the need to attach any sensors to the electrical devices.

In a remote or local environment in which a sensor network always collects data produced by sensors attached to physical objects, the engine presented here saves the data sent through the Internet and searches for data segments that correspond to real-world events by using natural language (NL) words in a query that are input in an web browser. The engine translates each query into a physical quantity representation searches for a sensor data segment that satisfies the representation, and sends back the event occurrence time, place, or related objects as a reply to the query to the remote or local environment in which the web browser displays them. The engine, which we expect to be one of the upcoming Internet services, exemplifies the concept of symbiosis that bridges the gaps between the real space and the digital space.

When using wearable computers used for medical operation and aviation safety, disrupted information presentation due to hardware/software problems can have serious consequences including medical accidents. We propose a mechanism that maintains information presentation in such situatoins by I/O device bypassing. In out method, I/O devices directly communicate with other devices if a system failure happens. The proposed method selects appropriate data converters by considering recognizability in order to present information that is easily understandable to users. We confirmed that the proposed method works effectively by implementing several applications with our prototype system.

This demo paper describes our daily activity sensing and recognition system with a wrist-worn sensor device called WristSense. The wrist-worn device is equipped with an accelerometer and camera, and can send the sensor data to a Bluetooth-enabled smart phone. With the accelerometer, we capture the wearer's hand postures and hand movements. With the camera, we capture visual information related to an object that the wearer is holding. An object that the wearer is using relates strongly to the activity that the wearer is performing. For example, an image (frame) including a coffee maker that is captured when the wearer is making coffee can be useful for recognizing the activity of making coffee. Also, a logger application on a phone records sounds related to daily activities. We use the sensor data in an attempt to recognize high-level daily activities that involve object use in real time.

In this paper we propose and implement a battery-shaped sensor node that can monitor the use of an electrical device into which it is inserted by sensing the electrical current passing through the device. We live surrounded by large numbers of electrical devices and frequently use them in our daily lives, and so we can estimate high-level daily activities by recognizing their use. Therefore, many ubiquitous and wearable sensing studies have attempted to recognize the use of electrical devices by attaching sensor nodes to the devices directly or by attaching multiple sensors to a user. With our node, we can easily monitor the use of an electrical device simply by inserting the node into the battery case of the device. We also propose a method that automatically identifies into which electrical device the sensor node is inserted and recognizes electrical events related to the device by analyzing the current sensor data. We evaluated our method by using sensor data obtained from three real houses and achieved very high identification and recognition accuracies.

This paper describes the development of a new finger-ring shaped sensor device with a coil of wire for recognizing the use of handheld electrical devices such as digital cameras, cellphones, electric toothbrushes, and hair dryers by sensing time-varying magnetic fields emitted by the devices. Recently, sensing the usage of home electrical devices has emerged as a promising area for activity recognition studies because we can estimate high-level daily activities by recognizing the use of electrical devices that exist ubiquitously in our daily lives. A feature of our approach is that we can recognize the use of electrical devices that are not connected to the home infrastructure without the need to equip them with sensors. We evaluated the performance of our approach by using sensor data obtained from real houses. We also investigated the portability of training data between different users.

This paper describes a toolkit for implementing lifelog applications that automatically generate web-based reports about daily lives from sensor data such as GPS data, acceleration data, and camera images that capture our daily activities. To design the toolkit, we collect example lifelog applications using a questionnaire survey where we ask participants what kinds of daily life data they want to record for later use and then clarify their characteristics. Based on the obtained information and our view, we realize an infrastructure that provides automatic report publishing and development support for generating reports from sensor data.

The new method proposed here recognizes the use of portable electrical devices such as digital cameras, cellphones, electric shavers, and video game players with hand-worn magnetic sensors by sensing the magnetic fields emitted by these devices. Because we live surrounded by large numbers of electrical devices and frequently use these devices, we can estimate high-level daily activities by recognizing the use of electrical devices. Therefore, many studies have attempted to recognize the use of electrical devices with such approaches as ubiquitous sensing and infrastructure-mediated sensing. A feature of our method is that we can recognize the use of electrical devices that are not connected to the home infrastructure without the need for any ubiquitous sensors attached to the devices. We evaluated the performance of our recognition method in real home environments, and confirmed that we could achieve highly accurate recognition with small numbers of hand-worn magnetic sensors.

This paper describes how we recognize activities of daily living (ADLs) with our designed sensor device, which is equipped with heterogeneous sensors such as a camera, a microphone, and an accelerometer and attached to a user's wrist. Specifically, capturing a space around the user's hand by employing the camera on the wrist mounted device enables us to recognize ADLs that involve the manual use of objects such as making tea or coffee and watering plant. Existing wearable sensor devices equipped only with a microphone and an accelerometer cannot recognize these ADLs without object embedded sensors. We also propose an ADL recognition method that takes privacy issues into account because the camera and microphone can capture aspects of a user's private life. We confirmed experimentally that the incorporation of a camera could significantly improve the accuracy of ADL recognition.

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.

Car navigation systems provide the best route to a destination quickly and effectively. However, during daily driving, this information is not necessary since drivers already know the route to the destination very well. In addition, it is time-consuming for drivers to input the destination. Thus, our research group has proposed a new car navigation system that provides information related to the destination by predicting the user's destination automatically. We propose the use of a new method that predicts the destination on the basis of the driving trajectory and the contexts in which the user drives. A system that uses our method knows the destination without user interaction and provides information related to the correct destination.

Accessing information when we are on the move is a key feature if mobile computing environments, and using an optical see-through head mounted display (HMD) is one of the most suitable ways to do this. Although the HMD can display information without interfering with the user’s view, when the sight behind the display is too complex or too bright, the information displayed can bee very difficult to see. To solve this problem, we have created a way of laying out information for the optical see-through HMD. The ideal area for displaying information is determined by evaluating the sight image behind the HMD captured by a pantoscopic camera mounted on it. Moreover, if there is no suitable area for displaying information, our method select involves using the sight image around users use to the ideal direction and instructing them to face the direction. Our method displays information to ideal areas.

In a ubiquitous computing environment, small computers attached to physical objects are required to send sensor data to many other nodes on a narrowband wireless network to provide various types of context-aware services. To reduce the cost of sending sensor data, this paper proposes a notation to indicate a pair of objects to share data with each other, based on the 'contact' relation between objects. We call this notation, contact-based notation (CbN). In our method, because each node can send data only to nodes contacting the node physically based on the notation, we can reduce both the distance between nodes and the amount of nodes to which to send data. Moreover, this paper describes an experiment conducted to examine the communication costs on each sensor node described in our proposed notation. The results show that the cost of our method is lower than the cost of the simple broadcasting method.

The method proposed here gathers data in high- density wireless sensor networks in real-time. It determines network topology by hierarchical clustering to avoid radio collision, which enables us to gather data with minimum data latency from numerous high-density sensor nodes. The analysis of our proposed tree-based data gathering protocol and real experiments using 39 real sensor nodes show that the proposed data gathering method can reduce data latency by hierarchical clustering.

In this paper, we propose a route planning method for mobile sensor nodes using cost map. The proposed method achieves novel route planning that can solve several practical problems from previous works: the limitations of sensing ranges, obstacles on the node's routes, and restriction of their movements. This method can determine the route that has the lowest power consumption. We also propose a sensing area defining method for dealing with many kinds of sensors. Furthermore, we compared the proposed method to A*algorithm, a well-known route planning algorithm. We implemented a prototype of the sensor node to verify our algorithm in a real environment.

Because of advances in information technologies, car navigation systems have come into widespread use as useful tools to guide drivers where they want to go. Conventional car navigation systems present the most suitable route according to a destination input into the system. However, since the required operation to input the destination costs so much, users do not usually use car navigation systems for daily driving. In this paper, to exploit the effective functions of car navigation systems, we propose a new system that automatically predicts user purpose and destination. The proposed car navigation system presents various information based on predicted purpose without interaction from users.

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 a new ubiquitous computing environment composed by visual markers and event-driven compact devices. We employ the VCC (visual computer communication) method, which we have already proposed as an information displaying method for visual markers. In the VCC method, a marker is composed of multiple tiles whose color changes at a certain interval of time, by which the marker can send dozens of bytes of information. In our research, to enhance the facility of VCC markers, we use rule-based compact devices to process various types of data and to change information shown in a VCC marker dynamically. The combination of VCC markers and compact devices enables various services such as the presentation of real-world information collected by compact devices and control of appliances via compact devices.

In this paper, we propose a new network topology discovery mechanism among ubiquitous chips, which are rule-based, event-driven input/output (I/O) control devices to compose ubiquitous computing environments. Since they achieve flexibility by describing behavior in a set of rules, we employ a rule-based approach to discover network topology. In ubiquitous computing environments, we use various communication methods and applications at the same time. Therefore, our flexible discovery mechanism works well in ubiquitous computing environments. Moreover, we verified our algorithm by implementing it on a topology discovery simulator and actual prototype devices of ubiquitous chips.

Because of the recent development of radio frequency identification (RFID) technologies, various systems for RFID tags have been proposed. Since RFID tags only have a simple function, i.e., sending data, they can be available for various purposes. Accordingly, by customizing RFID tag systems, we can expand their applications. However, previous systems have been usually proposed for one special purpose only. In this paper, we propose a rule-based RFID tag system using ubiquitous chips. Our previously proposed ubiquitous chips are rule-based I/O control devices. By applying rule-based principles, we can easily customize the RFID tag system and can construct flexible, scalable, and easy exploitable systems.

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.

People pay attention to fashion for various reasons. Wearable devices are useful in making fashion more expressive, especially by using LEDs, which can dynamically change their color or brightness using logic circuits or microcomputers. In this paper, we describe our design of prototype accessories, which use LEDs controlled via ultrasonic communication. The paper further reports a fashion show using the prototype accessories to make their usefulness clear.

In order to utilize the real world via computers by means of camera images in augmented reality systems, the concise coordinate information of the systems must be identified. Image-based approaches are promising for this purpose since they provide direct mapping from the camera images to the coordinate system for virtual objects, and therefore, no camera calibration is necessary. However, the conventional image-based markers are typically stickers, and the information they deliver is limited and susceptible to change dynamically. In this paper, we propose a location marking method, called VCC (visual computer communication), which uses more intelligent markers. In our method, a marker, consisting of 16 LEDs (light-emitting diodes), keeps blinking to provide both coordinate information and attached information such as an address or a URL.

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.

In wearable computing environments, an optical see-through head mounted display (HMD) is one of the most suitable wearable devices for displaying information. Although the HMD can display information without interfering with the user's view, the displayed information is difficult to see when the HMD background is too complex or too bright. We have created an information layout method for the optical see-through HMD that takes the background into account. It determines the ideal area for displaying objects by evaluating the HMD background captured by a camera.