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.

Sensor networks allow us to collect data, such as camera images, over a wide area. Understanding the sensing area by aggregating and processing the data from multiple sensors is promising. Deep Learning (DL) is a powerful method for interpreting data. However, communication cost on the sensor network and computational cost on the server are two substantial problems of aggregating and processing data from multiple sensors. We therefore propose divided processing of the DL between a server and a powerful Edge-Heavy Sensor (EHS). In our study, we reduced transmission data to twelve times lower than the amount of raw input data while maintaining a 4.5% decrease in the DL's recognition accuracy.

Recently, sensor devices such as temperature sensors or cameras are used for various purposes. These devices sometimes construct ad hoc networks, and a grid topology is one of their typical network topologies. Describing processing by rules is suitable for them since the system can flexibly change their processing according to their purposes. By relieving their rule processing loads and communication delay, the system can be applied for many applications. However, there is no rule processing schemes to realize those. In this paper, we propose a rule processing scheme using the Rete algorithm. Our proposed scheme can realize rule processing reducing redundant loads and delay for many applications.

This article proposes a new concept for a context-aware Web search method that automatically retrieves a webpage related to the daily activity that a user currently is engaged in and displays the page on nearby Internet-connected home appliances such as televisions. For example, when a user is washing a coffeemaker, a webpage is retrieved that includes tips such as “cleaning a coffee maker with vinegar removes stains well,” and the page is displayed on a nearby appliance. In this article, we design and implement a Web search method that employs ubiquitous sensors to monitor a user's daily life. Our proposed method automatically searches for a webpage related to a daily activity by using a query constructed from the use of daily objects employed in the activity that is detected with object-attached sensors. We evaluate the search method with real datasets collected from vast numbers of sensors and achieve very accurate webpage retrieval. We then investigate the usefulness and effectiveness of a daily life Web search with Wizard-of-Oz (WOz)-like experiments. We confirm that the presentation of webpages related to daily activities improves participants' future daily lives and triggers communication among the participants in the experiment.

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.

This paper proposes new concept of query free web search for daily living. We ordinarily benefit from additional information about our daily activities that we are currently engaged in. When washing a coffee maker, for example, we receive the benefit if we obtain such information as 'cleaning a coffee maker with vinegar removes its stain well.' Our proposed method automatically searches for a web page including such information relates to an activity of daily living when the activity is performed. We assume that wireless sensor nodes are attached to daily objects to detect object use; our method makes a query from the names of objects which are used. Then, the method retrieves a web page relates to the activity of daily living by using the query.

The environment generated media (EGM) are defined here as being generated from a massive amount of and/or incomprehensible environmental data by compressing them into averages or representative values and/or by converting them into such user-friendly media as text, figures, charts, and animations. As an application of EGM, an object-participation-type weblog is introduced, where anthropomorphic indoor objects with sensor nodes post weblog entries and comments about what happened to them in a sensor networked environment.

Assuming an environment in which a sensor network always collects data produced by sensors attached to physical objects, the demonstration system presented here searches sensor data for corresponding real-world events using a natural language (NL) words in a query. The system translates each query into a physical quantity representation also introduced here, searches for a sensor data segment that satisfies the description by the representation, and returns the information about the event that is reflected in time series of values from sensor readings.

In this paper, we introduce location traceability as an indicator for evaluating time-series location privacy for users on location-based services (LBS). The location traceability of a user is calculated with a formalized tree structure that represents all possible paths of a moving user. Through the results of the simulation experiments, we validated the effectiveness of this proposed indicator