Teruo Higashino

Osaka University | Handai · Graduate School of Information Science and Technology

Robust and accurate indoor localization has been the goal of several research efforts over the past decade. Towards achieving this goal, WiFi fingerprinting-based indoor localization systems have been proposed. However, fingerprinting involves significant effort; especially when done at high density; and needs to be repeated with any change in the...

Coronavirus disease 2019 (COVID-19) is still prevalent in the world. Social distancing is more important during exercise because we may not be able to wear masks to avoid breathing problems, heatstroke, etc. For supporting management of social distancing, we are developing a human localization system using a single camera especially for sports scho...

Controlling thermal environment in incubators is essential for premature infants because of the immaturity of neonatal thermoregulation. Currently, medical staff manually adjust the temperature in the incubator based on the neonatal skin temperature measured by a probe. However, the measurement by the probe is unreliable because the probe easily pe...

The Coronavirus disease 2019 (COVID-19) is still prevalent in the world. Exercise is important to maintain our health while dealing with infectious diseases. Social distancing is more important during exercise because we may not be able to wear masks to avoid breathing problems, heatstroke, etc. To maintain social distancing during exercise, we dev...

In this paper, we introduce a new problem setting for mobile robots based on backscatter-based communication and sensing. Ambient backscatter communication is a technology that transmits/receives data only by switching the impedance of the antenna at high speed without creating a carrier wave on the transmitting side (target backscatter tag). It mo...

In wheelchair basketball (WB), players are constantly trying to improve their wheelchair maneuvering techniques since these are the most basic and important actions in all situations. However, assessing maneuvering quality is difficult due to the lack of quantitative metrics. In this paper, we propose two classification methods for maneuvering acti...

Context recognition is a topic that has garnered considerable interest in the ubiquitous and pervasive computing research community. A wide variety of Internet-of-things devices with micro-electromechanical system (MEMS) sensors are used to obtain sensor data (e.g., acceleration, vibration, and sound) related to target contexts. However, devices fo...

In this paper, we propose FlowScan: a pedestrian flow estimation technique based on a dashboard camera. Grasping flows of people is important for various purposes such as city planning and event detection. FlowScan can estimate pedestrian flows on sidewalks without taking much cost. Currently, dashboard cameras have been becoming so popular for pre...

Some recent smartphone apps detect and predict dangerous situations and warn users. Since these apps detect users' situations by leveraging machine learning methods based on smartphone sensor data, a large amount of training data is required to construct detection models. However, it is difficult to collect such data, especially in dangerous situat...

Several attempts have been made to grasp three‐dimensional (3D) ground shape from a 3D point cloud generated by aerial vehicles, which help fast situation recognition. However, identifying such objects on the ground from a 3D point cloud, which consists of 3D coordinates and color information, is not straightforward due to the gap between the low‐l...

We have been working on automatic location estimation of HVACs utilizing the RSSI of BLE (Bluetooth Low Energy) to improve the time-consuming process in the HVAC system network setting where technicians need to identify the location of each HVAC one by one to assign a network address to the HVAC. This short paper particularly reports an initial att...

We present CrowdMeter: a participatory system that leverages the sensed data collected from users’ phones during their daily train commutes to gauge the real-time congestion level in railway stations. CrowdMeter tracks the passenger’s position in the station as well as identifies her/his context (e.g., waiting for a train, buying a ticket) along wi...

Location-based services in household enable not only estimating activities but also detecting the accident location of residents including children, parents and elderly people. Furthermore, home management systems make use of location information of residents for encouraging residents to live comfortably in their own homes. Passive infrared binary...

Tackling bottleneck and privacy issues of cloud computing, we attempt to push event stream processing down to devices which are currently empowered to compute and communicate at the edge of the networks. To accomplish that, we propose a self-organized task distribution framework that is composed of multiple brokers collaborating through our module-...

Due to the nature of smartphones' portability and mobility, many mobile apps are usually utilized in the real field environment using GPS, Wi-Fi and embedded sensors. For example, any navigation app uses GPS and Wi-Fi to locate the user in the map, and streaming apps may be used in cafeteria or even outside to satisfy the users' demand to watch soc...

We will demonstrate a mobile app test system in VR environments. The system enables developers to use a real smartphone in VR and to evaluate their apps at the locations of interest, with various network situations. The system consists of 2 core engines. First one is the real world reproduction engine which reproduces 3D city models and network env...

Water is the most vital nutrient in the human body accounting for about 60% of the body weight. To maintain optimal health, it is important for humans to consume a sufficient amount of fluids daily. Therefore, tracking the amount of human daily fluid intake has a myriad of health applications like dehydration prevention. In this paper, we present F...

Bluetooth Low Energy (BLE) is a promising technique for creating a cost-effective network to manage and control the BLE equipped equipment of buildings such as HVACs and lighting equipment, and the BLE network addresses can be used to identify the equipment. In order to enable the management (actuation and control) of equipment via BLE, each BLE ne...

We present CrowdMeter: a participatory system that leverages the sensed data collected from users’ phones during their daily train commutes to gauge the real-time congestion level in railway stations. CrowdMeter tracks the passenger’s position in the station as well as identifies her context (e.g., waiting for a train, buying a ticket) along her tr...

The progress of IoT technologies, which connect, control and operate everything in the physical world, is expected to realize secure and convenient societies and communities, and embodies a variety of smart city applications. However, not a few smart city applications are also "human-centric", which require individuals' and human crowds' locations...

Recently, sensing technology and Internet of Things (IoT) have much attention for designing and developing affluent and smart social systems. Although huge sensing data are collected in cloud, generally cloud systems are facing poor scalability and difficulty of real-time feedback. In this paper, we focus on geospatial sensing data welled out conti...

Toward the world of Internet of Things, people utilize knowledge from sensor streams in various kinds of smart applications. The number of sensing devices is rapidly increasing along with the amount of sensing data. Consequently, a bottleneck problem at the local gateway has attracted high concern. An example scenario is smart elderly houses in rur...

Water accounts for about 60% of the human body, and when the body loses it (e.g., through urine, sweat, etc.) in higher rate than its intake rate (through drinking), dehydration symptoms occur. The dehydration causes many severe health problems like organ and cognitive impairment. Therefore, it is critical for the human to drink water in a sustaine...

Increasing availability and usability enhancement of Wi-Fi in public areas has become more active. However, due to the dense deployment of Wi-Fi access points (APs), there is a chaotic and disorderly environment in urban areas. In our previous work, we have designed a function that predicts the network performance at each Wi-Fi AP according to the...

In this paper, we propose a method for logging micro-motion of in-home daily activity based on the skeleton recognition of the elderly in their daily life. We believe that in near future, many types of mobile robots will be spread to general household, and our idea is to let such a home robot be equipped with a 3D-depth camera such as Microsoft Kin...

Air conditioning in recent BEMS is now being highly automated, but providing true thermal comfort to building occupants and visitors is still challenging due to difficulty of sensing whole 3D space with limited number of sensors. In particular, thermal effect by crowd of people has not been considered so far in such automated air conditioning. This...

For real-time feedback and cost-efficient analysis from sport videos, it is essential to automatically identify players. In this paper, we propose a method for identifying sport players in videos. Our method uses wearable sensors to obtain their motions. Player identification is achieved by motion feature matching between (unknown) players in video...

Detecting aggressive driving behavior is essential for safe transport systems as it leads to the awareness of risks of accidents. Using smartphone-equipped sensors would be promising approach considering the penetration ratio to the consumers. In this paper, we have used a large dataset of accelerometer readings collected by smartphones of drivers....

We propose a method to estimate people travel modes and trajectories from control signal records (CSRs) generated at cellular base stations (BSs) when mobile phones send BSs any signal such as handover and data transmission. User locations can be roughly identified by BS IDs in the records as well as the locations of BSs. However, the location accu...

We present TransitLabel, a crowd-sensing system for automatic enrichment of transit stations indoor floorplans with different semantics like ticket vending machines, entrance gates, drink vending machines, platforms, cars' waiting lines, restrooms, lockers, waiting (sitting) areas, among others. Our key observations show that certain passengers' ac...

Most of the existing Rule-based Complex Event Process- ing(CEP) engines process all rules in a single set which might activate irrelevant copies of partial detected events every time new data comes. Against this issue, this paper analyzes the processing time of using one single set of rules and using two-steps matching where one complex rule is par...

Inertial Measurement Units (IMUs) embedded in commercial mobile devices are a good choice for continuous monitoring in healthcare domain due to their attractive form factor and low power consumption. We present improved and accurate sensing algorithms to sense basic events like step count, stride length, fall, and calorie, with accuracies better th...

Nowadays, many base stations (BSs) are equipped with batteries to provide services even during blackouts due to severe events such as disasters. In this paper, we propose a scheduling algorithm to adjust cell sizes, aka cell zooming, of battery-operated BSs in order for efficient use of energy. Our goal is to balance the tradeoff between user cover...

In this work, we present a novel approach to estimate core temperature with a wrist-worn sensor and ambient sensors. Our approach estimates core temperature by combining biological and ambient information with a human thermal model which formulates heat production in a body and heat transfer between human body core, skin, and the environment based...

This paper reports our recent result in designing a function for autonomous APs to estimate throughput and delay of its clients in 2.4GHz WiFi channels to support those APs' dynamic channel selection. Our function takes as inputs the traffic volume and strength of signals emitted from nearby interference APs as well as the target AP's traffic volum...

In many aspects of human activity, there has been a continuous struggle between the forces of centralization and decentralization. Computing exhibits the same phenomenon; we have gone from mainframes to PCs and local networks in the past, and over the last decade we have seen a centralization and consolidation of services and applications in data c...

In this paper we develop StationSense, a novel mobile sensing solution for precisely tracking temporal stop-and-go patterns of railway passengers. While such motion context serves as a promising enabler of various traveler support systems, we found through experiments in a major railway network in Japan that existing accelerometer-based passenger t...

A system to improve the quality of human life is developed and proposed. A model-based approach is used where smart home residents, appliances, energy sources and correlations among them are comprehensively modeled. The model was integrated with activity recognition information that enables the system to suggest smart life tips that provide advice...

In snowy countries, heavy snow has a large influence on traffic flows. Snow on urban roads disturbs traveling of vehicles as a huge amount of snow is piled up on roadsides, which often obstructs smooth driving. In this paper, we propose a novel method to predict the speed of vehicles on each road segment in snowy cities. This estimation is helpful...

Real-time context monitoring in public indoor space is a key technology for cyber-physical systems. Recent research studies have shown that analysis of geo-tagged multimedia data on social networking websites enables accurate detection and localization of 'events' in real world, which attract attention of a number of people (e.g., earthquakes). Alt...

This paper proposes a method of aggregating tempo-spatial data generated by sensors deployed in buildings or houses. The size of each sensor data such as temperature is usually small, but it often involves many additional data to represent its attribute values like time, location, data type and data precision. This would often increase the traffic...

Growing popularity of location-dependent mobile applications is continuously stimulating a demand for localization technology. However, in spite of significant research effort in the past decade, precise positioning in indoor environments is still an open problem. In this paper, we propose a novel type of indoor localization system that provides mo...

In this paper, we propose a non-invasive method to estimate core temperature based on a human thermal model considering individual differences using a wrist-watch wearable sensor. The method employs the two-node model to simulate the change of core and skin temperature by calculating heat exchange between core, skin and environment and heat product...

Monitoring body core temperature is important to prevent heat stroke. Core temperature is often measured as rectal or tympanic temperature which is difficult to monitor during activities. In this paper, we propose a method to estimate core temperature based on the two-node human thermal model by using wearable sensors. For accurate estimation, infe...

PrefaceThe target of the special issue was to receive submissions contributing to the hot topics on formal approaches for active and passive testing of distributed and networked systems. With this aim and after a careful selection, four papers have being chosen to be published in this special issue. In addition, the special issue includes a survey...