Cycle tourism is increasingly recognized as a means of regional revitalization worldwide. To support this trend, planning suitable cycling routes is essential. Especially, routes considering narrative, i.e., defined as the thematic and emotional coherence that links tourist spots into a meaningful story, are preferred by cycle tourists. However, traditional methods prioritize only physical intensity and route distances. To address this gap, we propose an AI-based system that generates narrative-rich cycling routes. Our proposed system gives the emotional features extracted from Points of Interest as narrative quality. Our evaluation revealed that our approach improved the narrative-aware route quality from 1.561 to 1.726 (increased by 10.6%).

In recent years, many surveillance cameras have been installed in cities, and human tracking technology has received much attention. In most current human-tracking technologies, servers collect images of people and then analyze their features from the data. In this method, the network loads on the servers increase as the number of people tracked increases, causing problems, such as packet loss and loss of real-time performance. In this paper, we propose two real-time human tracking methods. The methods conduct a human tracking process without servers by sharing extracted human features among devices. Experimental evaluations of the amount of communication traffic and processing time using multiple cameras have shown that the two proposed methods can distribute the network load with slight deterioration in processing speed and tracking accuracy.

In recent years, the use of computer systems for identifying people has become increasingly popular. Clear facial images and detailed facial features are often provided to the system to improve identification accuracy, but if they are misused, privacy can be compromised. The authors are currently building a next-generation video blog system that can do the following: capture images of passersby with cameras, blur the facial images of all the people, remove the blurring for specific people who have registered their facial images for public viewing, and then upload them as video blogs in real time in a hands-free manner. By comparing the similarities between the obscured data in the user's stored data and the data captured by the camera and immediately obscured and sent to the edge server, the authors devised a system that enables person identification but does not pass clear facial images and features to the system. The authors focused on the possibility of using noise strength added to features and random seeding of features as a common quasi-encryption key to protect privacy. This paper assesses the extent to which the intensity of noise in this system obscures person identification. The results show that privacy can be protected by adding epsilon noise below a certain strength to the features, and the noise strength and the random number seed for noise generation can be used as a common quasi-cryptographic key.

In recent years, there has been an urgent need to improve safety and efficiency to avoid dangerous situations. In this paper, the authors proposes a visualization system of near-future information by augmented reality (AR) to avoid dangerous situations. The proposed system utilizes the position and speed information of the user and obstacles, predicts crashes, and recommends avoidance actions such as changing course or stopping. Experiments were conducted under different conditions by the implemented system to determine how many seconds into the future it would be safer for the user and easier to take avoidance action. The experiment results showed that the avoidance rate was almost the same for 2 seconds or longer, but the best rate was for 3 seconds ahead.

Due to the recent popularity of sports bicycles, many people have started tourism with cycling. Beginner cyclists often try to complete long distance cycling without sufficient training, causing overuse of leg muscles. Overuse of leg muscles caused by an irregular bicycle riding form leads to diseases such as iliotibial band syndrome. It is helpful to automatically identify beginner cyclists of irregular forms to avoid these diseases. However, none of the multimodal AI models recently attracting attention can achieve this. This paper proposes a system architecture for detecting individually optimized irregular bicycle riding form. Our proposed architecture uses bicycles installed with the Inertial Measurement Unit (IMU) and 2D Light Detection and Ranging (2D LiDAR) sensors. The sensor data obtained from IMU are analyzed by Recurrent Neural Network-based models, and the results are refined by multimodal classifier models combined with the 2D LiDAR data. The model selected by the proposed method obtained 0.900 in accuracy, 0.892 in precision, and 0.841 in recall for an f-score of 0.862, demonstrating the effectiveness of meta-model approaches.

Recent technological advances in Virtual Reality (VR) and Augmented Reality (AR) enable users to experience a high-quality virtual world. Using VR to experience the virtual world, the user's entire view becomes the virtual world, and the user's physical movement is generally limited because the user cannot see the surrounding situation in the real world. Using AR to experience the virtual world, we generally use special sensors such as LiDAR to detect the real space and superimpose the virtual world on the real space. However, it is difficult for devices without such special sensors to detect real space and superimpose a virtual world at an appropriate position. This study proposes two methods for replacing the background: a method using depth estimation and a method using semantic segmentation. This study also confirmed that the system can be used with sufficient removal accuracy and response time by using appropriate image size for the environment and that a safe and highly immersive virtual world experience can be achieved.

In this paper, the authors propose a real-time AR visualization system that enables the user to visually grasp the future snow-covered situation at the current location, aiming to support residents and visitors in heavy snow areas. The proposed system generates snow-covered spatial information that reflects the snow-covered situation on spatial information in the real world sensed by 3D LiDAR, and composes it on the video image captured by a camera. This paper describes a lightweight method of spatial information processing by reducing the amount of spatial data transmission.

In this paper, we propose a tree construction method to collect and composite distributed videos on the live broad-casting system called “same world broadcasting system”. The same world broadcasting system generates and delivers a video in which video objects captured at the different places are displayed as if they were located in the same world. Our tree construction method employs an “occlusion graph” that represents the overlap relations of the video objects to give a heuristic solution to find a tree of network structure to collect and composite videos which provides a high-quality video in heterogeneous environments. We implemented the tree construction algorithm and conducted computer simulations considering different scenarios. Our simulation results show that our proposal can find a good collection tree within a practical amount of time.

Recent technological advances in Virtual Reality (VR) and Augmented Reality (AR) enable users to experience a high-quality virtual world. In VR applications, the user's physical movement is generally restricted because the situation around the real world cannot be seen. AR allows users to experience virtual worlds without restrictions on physical movement, but the extent to which they are replaced as virtual worlds is limited. In this research, assuming the use of smartphones and tablet devices, a partial virtual world system is implemented by removing only the background part from the real-time real-world image taken by the camera and replacing it with a virtual background.

One of the research issues for stream data is fast notification of continuous query results. Recent researches assume that query processing servers receive data from remote data sources continuously. Therefore, when a large number of processing servers are distributed in networks, large amounts of communication traffic for those are produced. This is the main cause of delaying query result notifications. To tackle this fundamental problem, we focus on the conjunction of operations and conditions in continuous queries for distributed processing systems. When queries consist of some series of operations and conditions, processing servers can stop query executions if the remaining operations or condition checking are dispensable. Thus, communications less arise and communication traffic is further reduced. Our proposed system represents continuous queries by conjunctive normal forms (CNF queries). The proposed system constructs trigger trees for evaluating the sum terms of CNF queries and determines the timing for their evaluations, in order to reduce communication traffic. We confirmed that one of the proposed methods can reduce the average amount of communication traffic by 23 percent compared with a sensor data serial aggregation method in an evaluation situation.

As an important foundation of the smart city, MaaS (Mobility as a Service) provides a seamless passenger experience using multiple modes of transport from the beginning until the end of a journey, and its developments have attracted keen interest from the industry in recent years [1] [2] . Furthermore, as the last mile of the MaaS, electric bicycle is an important and environmental-friendly transportation [3] [4] .

Many systems and services for VR spaces use avatars to represent the appearances of each user. In those systems and services, the users communicate with each other via their avatars. Currently, various techniques and researches have been studied for avatar appearance. However, the existing techniques and studies mainly regard avatars as the self-expression of each user and do not mention the influences on communication from others. In communication content, avatars are one of self-expression of each user and one of the communication tools. Therefore, this paper describes an investigation of how avatar appearances affect communication from others. The result from the research showed that the degree of deformation of avatars affects communication from others in various situations such as informal and formal situations.

Recently, live video broadcasting is frequently used due to the COVID-19 pandemic. More realistic and comfortable experiments can be realized if multiple real-time videos from different places are displayed on a single screen. This paper calls such live broadcasting "same world broadcasting" as if all objects exist in the same space. In this paper, we propose a distributed system for the same world broadcasting. We evaluate the proposed system using the experimental implementation in a LAN environment and an open testbed environment. The experiment results show that the proposed system can reduce the processing time to collect and compose many real-time videos.

Due to the increase in the speed of wireless communication in recent years, video-on-demand (VoD) systems has got great attention. In conventional VoD systems, when the number of clients receiving video data increases, the problems of longer playback interruptions or longer buffering times occur. Accordingly, several research focus on the VoD systems that adopt broadcast-type distribution (B-VoD). In B-VoD systems, video files are divided into several parts and distribution servers broadcast them in the sequences of predetermined broadcast schedules to reduce interruption time. However, conventional broadcasting methods do not consider the issues that occur in actual B-VoD systems, such as initial buffering delay and the increases of data sizes caused by video file division. Interruption time can be further reduced by considering them. Hence, in this research, we propose a data segment scheduling method for B-VoD systems. We measure the performance of our proposed method on an actual B-VoD system utilizing radio broadcasting (VHF-band) to achieve a broadcast-type distribution. The results of the experiments confirmed that, under the condition of an uninterrupted playback, the waiting time until the start of a playback can be reduced by up to 85% under our proposed method by dividing the requested video data into 6 parts and broadcasting the parts in parallel.

This paper proposes "WoT-based Logical Sensor Architecture (WLSA)," a novel virtual sensor architecture on the basis of Web of Thing (WoT) that enables IoT applications to treat the sensor data and processing results in a uniform way in edge computing environments. WLSA reduces the computing and network resources required for the IoT applications by reusing the processing results in multiple data flows. This paper also proposes a data flow transforming (DFT) algorithm, in which a subset of the data flow is automatically replaced with a process that reuses the result of running processes so that the application developers do not need to conscious of sharing the processing result. We have implemented a prototype system and an object detection application based on WLSA using Node-RED data flow processing framework in an edge computing environment and evaluated its effectiveness. The evaluation results showed that WLSA reduced the execution time with less usage of computing resources. The prototype could accommodate 20 applications with less than 100 ms response time under 4% CPU usage.

Due to the recent popularization of live video distributions, live video distributors such as YouTubers have attracted great attention. Some of them shoot videos of themselves using smartphones while moving and distribute the videos via the Internet. One of the major consideration points of live video distributions on the Internet is trust between distributors and viewers, since various public concerns such as threats or attacks to distributors occur in live video distribution situations with no trust. To solve these concerns and enable safety live video distributions on the Internet, we propose a novel live video distribution architecture. In trusty situations, the systems under our proposed architecture add more video captions to give various information to the viewers. Otherwise, the systems add more effects to hide information. We also define three policies for distributors to manage trust.

In IoT (Internet of Things) systems, various devices such as cameras and sensors generate a huge stream data and are cyclically send them to processing computers via computer networks. The transaction rates for processing such stream data is one of the main performances for some IoT applications. Some schemes control transaction intervals to improve transaction rates. Most of them adopt a simple approach in that processing computers request the changes of transaction intervals to data sources every a fixed number of transactions. This approach unfortunately causes the drawback of unfair (inconstant) transaction intervals. Most of IoT applications prefer constant transaction intervals, e.g., a constant frame rate for video applications, since their constantness enable stable processing. In this paper, we propose a method to dynamically determine transaction intervals based on transaction rates. In our proposed method, the processing computer for an IoT application changes the transaction interval when the average value for some previous transactions largely changes. We measured the transaction rate of our proposed method in our developed simulator and confirmed that our proposed method can give a higher fairness of the transaction rates compared with existing methods by using appropriate parameters.

We can get real-world information (social sensor data) by analyzing posts on social networking services (SNSs), which have become popular in recent years. We are studying and developing a system to generate and share social sensor data and social sensors (programs to analyze posts on SNSs) among users. Descriptions of previously created social sensors such as analysis programs are helpful for creations of new social sensors. When users search previously created social sensors in conventional S^3 systems, search results are shown in list form without indicating relevances between social sensors. Therefore, users need to check descriptions of many social sensors until finding helpful descriptions. This annoys users to create new social sensors. By reducing the number of social sensors to be checked, users can find helpful descriptions easier. In this research to achieve fast search, we designed and implemented a system to visualize relevances between social sensors. The proposed system regards that previously referenced social sensors are relevant and also that social sensors with high similarity in descriptions are relevant. The proposed visualization system shows relevances between social sensors by representing social sensors as nodes connected to their referenced social sensors by edges.

Internet live broadcasting services such as USTREAM, TwitCasting have become popular. These services give broadcasters an ability which can broadcast videos via the Internet. By adding video effects and audio effects, live streaming services can realize as if broadcasters were in a different world. In this paper, we call this kind of live streaming `Different Worlds Broadcasting'. However if many viewers request the effect in a short period of time or use some heavy load effect, it takes much time to render those effects and the frame rate gets worse. Therefore, currently users can use only small load effects such as superimposing small firework effect on the video, adding simple echo effect on the sound. Rendering effects in a short time, users can add more effects or the frame rate cat get better. In this paper, we propose a distributed video processing system for Internet live broadcasting services with video effect and audio effect. The proposed system take a video by broadcaster's PC or smartphone and transmit it to effect servers to add various effects. Effected video stream is transmitted to the broadcast server of the Internet live broadcasting service.

Due to the spread of smartphones and tablet devices, many photographs are uploaded and shared on the Internet. Cameras often have sensors such as GPS and digital compass. These sensor data are attached to photograph data as metadata. Metadata is helpful to retrieve photographs that show the designated points. For this request, existing systems search the photographs taken in constant distance from the designated points and show them to the users. However, some of them do not cover the designated point when their photographing orientations are largely different from the direction for the point or obstacles hide the point. So, the users often check many photographs to find their desirable photographs showing the designated points. In this paper, we propose a method to calculate the probability that photographs show the designated points. By showing the photographs that have high scores with priority, the users can find their desirable photographs with less checking. Also, we develop a system to retrieve photographs using our proposed scoring method.

In this paper, we propose a lightweight multi-receiver encryption scheme for the device to device communications on Internet of Things (IoT) applications. In order for the individual user to control the disclosure range of his/her own data directly and to prevent sensitive personal data disclosure to the trusted third party, the proposed scheme uses device-generated public keys. For mutual authentication, third party generates Schnorr-like lightweight identity-based partial private keys for users. The proposed scheme provides source authentication, message integrity, replay-attack prevention and implicit user authentication. In addition to more security properties, computation expensive pairing operations are eliminated to achieve less time usage for both sender and receiver, which is favourable property for IoT applications. In this paper, we showed a proof of security of our scheme, computational cost comparison and experimental performance evaluations. We implemented our proposed scheme on real embedded Android devices and confirmed that it achieves less time cost for both encryption and decryption comparing with the existing most efficient certificate-based multi-receiver encryption scheme and certificateless multi-receiver encryption scheme.

In this paper, we propose a novel efficient sensor data stream recovery scheme called "synchronized recovery stream merging (SRSM)," for reliable event-driven IoT applications, assuming multicast delivery of data streams. SRSM synchronizes and merges multiple data streams for recovery by waiting for other data streams keeping the delivery data order, as long as the required restriction for delivery latency is satisfied. SRSM reduces the number of streams required to generate and send on the data stream sender dramatically than applying an existing stream merging scheme for recovery, thus enables to save the network bandwidth of the sender. Through extensive simulations, we evaluated the performance of SRSM and confirmed that about 48% - 60% network bandwidth was saved on the sender in the frequent failure situation compared to the existing schemes, keeping the average satisfy rate of requested delivery latency.

The recent development of stream delivery technology made Internet broadcasting services popular. In live Internet broadcasting, broadcasters or viewers often add video or sound effects (we call this kind of live broadcasting, `different worlds broadcasting'). Therefore, we have proposed a distributed Internet live broadcasting system with video and audio effects. In this paper, we describe the implementation of our proposed system and its demonstration system using real-time facial animation.

Summary The feasibility of using embedded systems in real‐life applications is becoming more widespread. These applications have grown from do‐it‐yourself projects of computer enthusiasts or robotics projects to larger scale efforts and deployments. This paper describes a scenario that deployed a prototype application that allows the public to interact with features of a model and view videos from a first‐person perspective on the train. Through testing the embedded systems and their usage in a public setting, it was demonstrated that interactive features could be implemented in model train exhibits, which are featured in traditional museum environments that lack technical infrastructure. Specifically, the Arduino and Raspberry Pi provide the necessary linkages between the Internet and hardware, allowing for a greater interactive experience for museum visitors. These results provide an important use‐case scenario and lessons learned that cultural heritage institutions can use when implementing embedded systems on a larger scale, for the purpose of increasing visitors' experience through greater interaction and engagement.

Recently, IoT (Internet of Things) environments have begun to attract a great deal of attention. In IoT environments, various “things”, such as sensors, are connected to the Internet and act as distributed data sources to continuously generate big data (stream data). One of the main research issues for such stream data is fast execution of continuous queries. Most conventional schemes assume that processing servers receive data streams from remote data sources. Therefore, when large numbers of data sources are distributed in IoT environments, large amounts of communications traffic from those data sources are produced. This is the main cause of long stream processing times. To tackle this key problem, we take this feature of IoT environments into account and try to reduce the stream processing time by reducing the stream processing load. Our proposed scheme extracts conditional expressions, and determines the order of evaluation of these expressions, in order to reduce processing and communication loads. Our evaluation shows that the proposed scheme can reduce the maximum number of communication hops and the average amount of communication traffic in IoT environments.

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.

Due to the recent popularization of digital broadcasting systems, clients can have several types of watching contents. In addition, area-based broadcasting using the bandwidth that is not used in radio broadcasting has attracted great attention. In area-based network environment, the server can deliver continuous media data such as audio and video to clients in a limited area. In area-based broadcasting, since the server delivers data repeatedly, clients have to wait until their data are broadcast. To reduce the waiting time, many studies employ the division based broadcasting technique, which reduces waiting time by dividing the data into several segments and frequently broadcasting the precedent segments. When the server makes the broadcast schedule in area-based broadcasting, it needs to consider both loading times of highlight scene and main scene. In broadcasting, since playing time of the commercial contents is predetermined, the server needs to make the broadcast schedule according to the consumption rate and the number of channels by setting both loading times of the highlight scene and the main scene. In this paper, we propose a scheduling method considering loading time for area-based broadcasting. In our scheduling method, since the server makes the broadcast schedule using a different ratio of dividing data for the highlight scene and the main scene respectively, waiting time is reduced effectively.

Due to the recent development of digital TV broadcasting systems, Near Video-on-Demand (NVoD) systems has attracted a great attention. In general NVoD systems, the server broadcasts the same data repetitively and clients have to wait until they finish receiving data and play it. To reduce this waiting time, many researches have proposed the scheduling methods that divide the data into several segments and frequently broadcast the precedent segments. These scheduling methods suppose only the case of which a single client receives data. In the actual networks, we need to make the broadcast schedule in heterogeneous clients' environments that the available bandwidth for clients differs. Although we have been proposed the scheduling method in heterogeneous clients' environments, our conventional method does not consider the case in which there are many types of clients. In this paper, we propose a scheduling method to reduce the waiting time for many types of clients. Our scheduling method expands the availability of our conventional method and reduces the waiting time by producing an effective broadcast schedule based on the number of client types and the available bandwidth.

In recent years, video-on-demand services such as YouTube or Hulu have become popular. These VoD services often adopt P2P (Peer-to-Peer) streaming techniques to manage many users' requests. Some services provide different quality services for the users. For example, the users who pay money for the service provider can watch high-quality videos, and others can only watch low-quality videos. In such a multiple bit rate video delivery, since high-quality videos have high bit rate, their interruption time is very long compared with that for low-quality videos when many peers watch high-quality videos. In this paper, we propose a method to reduce interruption time for users watching high-quality videos in multiple bit rate video delivery. Our evaluation results show that our proposed method can reduce their interruption times.

Due to the recent popularization of digital broadcasting systems, selective contents broadcasting depending on users' preferences with node relay-based web cast have attracted much attention. In node relay-based web cast, waiting time is reduced by receiving contents from several nodes. However, when a node that delivers contents disconnects from the network or reconnects to it while delivering contents, waiting time increases by changing a delivery schedule. In this paper, we propose a scheduling method considering reconnection on selective contents delivery with node relay-based web cast that relay data among nodes. Our proposed method reduces waiting time by restructuring the delivery schedule considering the disconnection and the reconnection of the node.

Due to the prevalence of sensors such as live cameras or environmental sensors, sensor data stream delivery, which requires continuous and cyclic data delivery attracts great attention. For sensor data stream delivery, various communication loads balancing techniques have been studied since the load of the sensor data source become high to accommodate large number of clients. However, these studies assume only the requests that have the same collection cycle, which is not enough for the actual applications. In this paper, we propose a sensor data stream delivery system with communication loads balancing for heterogeneous collection cycle requests. The proposed system distributes the loads by re-delivering the sensor data that are requested by other clients with different collection cycles but have common cycles.

Due to the recent development of digital TV broadcasting systems, Near Video-on-Demand (NVoD) systems has attracted a great deal of attention. In general NVoD systems, the server broadcasts the same data repetitively and clients wait until the first portion of the data is broadcast. Although there are many studies on how to reduce the waiting time, these studies assume that there is only one type of clients, and they do not consider cases in which there are many types of clients such as mobile phones, digital video receivers, and so on. In such cases, these methods cannot reduce the waiting time effectively because the available band-widths for clients differ depending on their performances. In this paper, we propose a scheduling method to reduce the waiting time considering heterogeneous clients. Our proposed method further reduces the waiting time by producing an effective broadcast schedule considering the number of clients' available channels.

Increased global interest in environmental issues has led to demands for power consumption reduction of home electronics. Home energy management systems (HEMS) achieve this by monitoring and controlling the power consumption of home electronics. To reduce power consumption adequately, we need to flexibly customize HEMS based on user policies. However, conventional HEMS are completely systematized and it is difficult to customize them. Conventional HEMS lack versatility. In this paper, we develop a toolkit for constructing HEMS. Our developed toolkit adopts rule-based description for monitoring and controlling the power consumption of home electronics. Since we can easily customize HEMS by changing rules, our developed toolkit can provide versatility.

Due to the continued popularization of broadcast and communications integration environments, streaming delivery using broadcast and communication is attracting great attention. In streaming delivery on an environment, clients concurrently receive such data as music or movies from both broadcasting and communication systems. Although conventional methods reduce the interruption time, they fail to consider the upper limit in the available bandwidth. In this paper, we propose a delivery method that reduces the interruption time by considering the number of clients. Our proposed method reduces the interruption time by setting the bandwidths of the broadcast and communication systems and making a delivery schedule.

Due to the recent popularization of digital webcast systems. close-range broadcasting using continuous media data, i.e. audio and video, has attracted great attention. For example, in a movie program, after a user watches interesting content such as a highlight scene, he/she will watch the main program continuously. In close-range broadcasting, the necessary bandwidth for continuously playing the two types of data increases. Conventional methods reduce the necessary bandwidth by producing an effective broadcast schedule for continuous media data. However, these methods do not consider the broadcast schedule for two types of continuous media data. When two types of continuous media data are scheduled, waiting time that occurs from finishing the highlight scene to starting the main scene may increase. In this paper, we propose a scheduling method to reduce the waiting time for close-range broadcasting. In our proposed method, by dividing two types of data and producing an effective broadcast schedule considering the available bandwidth, we can effectively reduce the waiting time.

Most of the recent set-top boxes for digital video broadcasting can connect to the Internet. They can receive data from broadcast systems and from communication systems. Since such hybrid video broadcasting environments are suitable for large-scale streaming delivery, several schemes to reduce interruption time which occurs while playing video in hybrid broadcasting environments have been proposed. However, these schemes do not create sophisticated broadcast schedules. By dividing video data into several segments and broadcasting them according to an effective broadcast schedule, we can further reduce interruption time. In this paper, we propose an interruption time reduction scheme for hybrid video broadcasting environments. Our proposed scheme exploits the division-based broadcasting technique. In the division-based broadcasting technique, segments are broadcast so that clients can receive them until the time to play each of them. Also, we consider the prefetch of video data. By these techniques, we reduce interruption time effectively. Our simulation experiments revealed that our proposed scheme could reduce interruption time further than conventional schemes.

Due to the continued popularization of broadcast and communications integration environments, streaming delivery using broadcast and communication is attracting attention. In streaming delivery on the environment, clients concurrently receive streaming data such as music or movies from broadcasting and communication systems. Although these systems compensate for the demerits of each other, the interruption time is lengthened if the system does not deliver the data efficiently. In our proposed method, the system produces a broadcast schedule of streaming data that considers communication bandwidth. In this research, we confirmed that extra bandwidth that gives shorter interruption time differs from communication bandwidth. Our proposed method reduces the interruption time by finding the extra bandwidth.

Due to the continued spread of the Internet, delivering continuous media data, i.e., audio and video, has attracted great attention. In broadcasting systems, clients generally have to wait until their desired data are broadcast. Therefore, many researches have addressed ways to reduce waiting time. Although several methods to reduce waiting time in continuous media data broadcasting have been proposed, they have failed to consider cases where the server broadcasts Internet advertisements while playing the data. In this paper, we propose a scheduling method to reduce the waiting time that considers Internet advertisements. In our proposed method, by dividing the data and producing an effective broadcasting schedule based on the playing time of Internet advertisements, waiting time is reduced.

In recent years, there has been an increasing interest in a broadcast database system where the server periodically broadcasts contents of a database to mobile clients such as PDAs and smart phones. There are three query processing methods in the broadcast database system. Generally, mobile clients have limits in energy consumption, i.e., battery,and each of the three methods consumes different amount of energy for query processing. In this paper, we propose a new method which dynamically chooses one of the three query processing methods considering energy consumption.

Due to the development of sensing technologies, sensor stream processing systems have been getting great attention. Sensor stream processing systems enable us to recognize the state of objects. For example, attach an acceleration sensor to a man and the system beforehand stores sample sensor data for the manpsilas walking and standing states. By comparing the current data stream with the stored sample data, the system can recognize whether he is walking or standing. Recognizable states increases in proportion to the number of the sample data. However, the processing time lengthens as the number of sample data increases. Long processing time is impractical for data stream processing systems. In this paper, we design and implement a data stream processing system using dynamic time warping (DTW) distance. DTW is robust for changes in time and often used for streaming data analysis. In our implemented system, we reduce the processing time by parallelizing the calculation of the DTW distance.

This paper introduces a sensor network testbed, X-sensor, that integrates multiple sensor networks deployed at different sites. X-sensor provides three functionalities: (a) a sensor network search which enables users to find a sensor networks appropriate for experiment and data acquisition, (b) a sensor data archive which provides users with various sensor data acquired by sensor nodes, and (c) an experimental testbed which enables remote users to evaluate their proposed methodologies.

In recent years, there has been an increasing interest in sensor networks, in which sensor nodes such as temperature or humidity sensors communicate with each other for environmental monitoring and so on. In sensor networks, it is important to reduce the energy consumption, since sensor nodes have limits in battery. Most researches achieve this by reducing sensor amount of transmitted data. However, there is a problem that the amount of transmitted data become large and their energy consumption becomes high when there are a lot of nodes in the sensing area. To solve the problem, we previously proposed a data gathering method. In this method, the data sink estimates the data value of nodes, broadcasts the estimated values, and then, sensor nodes whose observed values are largely different from the estimated values send the data. However, this method has a problem that it cannot sufficiently reduce the energy consumption. In this paper, we propose a new broadcast-based data gathering method. In this method, the data sink reduces the nodes which send their observed values when the reliability of gathered values by the data sink is high.

Due to the recent popularization of digital broadcasting systems, selective contents broadcasting depending on users' preferences have attracted great attention. For example, in a quiz program, a user selects his or her answer and watches the video content for the answer. Although the server can deliver programs reflecting users' preferences, clients have to wait until their selected contents start playing. Conventional methods reduce the waiting time by producing an effective broadcast schedule. However, the server has to deliver several content items so that users have choices. This requires more bandwidth than for non-selective contents. In this paper, we propose a method to reduce the waiting time considering user behavior on selective contents broadcasting with node relay-based webcast that relays data among nodes. When a client pulls out of the network while delivering contents, our proposed method reduces waiting time by selecting other clients and reconstructing a broadcast schedule considering the available bandwidth of each client.

Recently, streaming systems with Peer-to-Peer (P2P) technology have attracted much attention and are changing how we watch movies. In P2P streaming systems, a peer that plays the movie receives data from other peers. By playing the received data sequentially, the user can watch the entire movie from beginning to end. In conventional methods, by receiving the first chunk of data sequentially from a peer with large bandwidth, the waiting time is reduced effectively. However, they do not consider the case where heterogeneous peers deliver data to multiple peers. In this paper, we propose a method to reduce the waiting time for selecting peers on P2P streaming by selecting peers considering the available bandwidth. Our evaluation shows that our proposed method reduces the average waiting time 62.5% more than conventional methods at maximum.

We report the system that collects the data from the sensor network and visualizes the data on real time by three dimensions on a computer. It becomes possible for this system to make a user make the measurement data on space intuitive.

Due to the recent popularization of digital broadcasting systems, selective contents, i.e., watching contents users selected themselves, have attracted great attention. For example, in a news program, after a user selects the desired content, he/she watches it. In selective contents broadcasting, since the server needs to deliver many contents, the necessary bandwidth for playing the data without interruptions increases. Although conventional methods reduce necessary bandwidth, they do not consider the upper limit in the bandwidth. When upper limit exists in the bandwidth, users have to wait to receive the data. In this paper, we propose a scheduling method to reduce waiting time by considering available bandwidth. In our proposed method, by acquiring the bandwidth that is the same as the data consumption rate, waiting time is effectively reduced.

Recently, immersive projection technology (IPT) systems such as CAVE and CABIN have attracted great attention. In IPT systems, since we can experience virtual environments with whole body, these can provide high immersive virtual environments. To interact with virtual environments easily, IPT systems often adopt one-handed input systems. However, by using bimanual input systems, their operationality, e.g., walking-through and pointing, can be improved. Although there are several bimanual input systems for virtual environments, these have not been used for IPT systems. In this paper, we propose a bimanual input system for IPT systems. In our proposed system, users wear compact joysticks on both hands and their hands' positions are detected by magnetic sensors. By using the system, users can interact with the virtual environment in the IPT system. From our evaluations, we confirmed that our proposed system provides fast and easy operations in virtual environments.

Recently, grid computing, which exploits extra computing resources, has attracted great attention. In grid computing environment, generally, by using several clients and calculating different equations against the large data generated by a server, the computation time is reduced. However, in the case where the number of clients is large, the system load becomes high and the computation time can become long. In this paper, we propose a delivering method to reduce the computation time using broadcasting delivery. In broadcasting delivery, the server broadcasts the data to many clients concurrently. Accordingly, the system load does not change even if the number of clients increases. Although clients have to wait until their desired data are broadcast, our evaluations show that we can reduce the computation time by dividing the data into only two segments.

Due to the recent popularization of digital broadcasting systems, broadcasting continuous media data such as music or movies has attracted much attention. In general continuous media data broadcasting, since clients have to wait to receive data before playing it, various methods to reduce waiting time have been studied. Some reduce the waiting time by dividing the data into several segments and broadcasting precedent segments frequently with a single channel. However, by dividing the data into finer segments and producing an effective broadcast schedule, the waiting time can be further reduced. In this paper, we propose an effective scheduling method to reduce waiting time with finer data division

Due to the recent prevalence of digital broadcasting, various schemes for broadcasting continuous media data, such as music or movies, have been studied. However, most of these studies cannot enable fast-forward operations. That is, when a user fast-forwards data, the client cannot play the data continuously. We propose a scheme to enable fast-forward operations. Our proposed scheme, which is based on the CHB (cautious harmonic broadcasting) scheme, reduces the waiting time of clients under the condition that clients can play the data without interruptions until its end, even when a user fast-forwards it.