Hiroki Ishizuka

A DTN-Based Sensor Data Gathering for Agricultural Applications

This paper presents our field experience in data collection from remote sensors. By letting tractors, farmers, and sensors have short-range radio communication devices with delay-disruption tolerant networking (DTN), we can collect data from those sensors to our central database. Although, several implementations have been made with cellular phones or mesh networks in the past, DTN-based systems for such applications are still under explored. The main objective of this paper is to present our practical implementation and experiences in DTN-based data collection from remote sensors. The software, which we have developed for this research, has about 50 kbyte footprint, which is much smaller than any other DTN implementation. We carried out an experiment with 39 DTN nodes at the University of Tokyo assuming an agricultural scenario. They achieved 99.8% success rate for data gathering with moderate latency, showing sufficient usefulness in data granularity.

Live E! Project: Establishment of Infrastructure Sharing Environmental Information

The Live E! project is an open research consortium among industry and academia to explore the platform to share the digital information related with the Earth and our living environment. We have getting a lot of low cost sensor nodes with Internet connectivity. The deployment of broadband and ubiquitous networks will enable autonomous and global digital information sharing over the globe. In this paper, we describe the technical and operational overview of Live E! project, while discussing the objective, such as education, disaster protection/reduction/recovery or business cases, and goal of this project activity

A field experience on DTN-based sensor data gathering in agricultural scenarios

This paper describes our field experience on data collection from remote sensors. By letting tractors, farmers and sensors have short-range radio communication device with delay-disruption tolerant networking (DTN), we can collect data from those remote sensors to our central database. Although, several implementations have been made by using PHS devices or mesh network in the past, DTN-based systems for such applications are still under explored. The main contribution of this paper is to present our practical implementation and experiences on DTN-based data collection from remote sensors. The software, which we have developed for this research, is very small - only about 3000 lines in C, which is much smaller than any other DTN implementations. We carried out an experiment with 10 DTN nodes in the University of Tokyo. They achieved 100% collection with moderate delivery latency showing sufficient usefulness in data granularity.

Collecting Adaptive Data for Isolated Wireless Sensors with Patrol Nodes in Live E

Recently, Technology of sensor networks develops rapidly. In addition, people have started utilizing many kinds of sensors. Sensors independently collect environmental information all over the world. Unfortunately those sensed data are not shared and open to the public. Therefore, we have constructed super-large-scale sensor network system to share sensed data collected from sensors all over the world. We call such a project Live E!. In a part of Live E!, To sense a public area in whole, we assume public objects(mailbox, bus stop, dumpster) uniformly allocate in a district evenly is equipped with a sensor and a wireless device. The public objects often dose not have connectivity to a network. Those are Isolated Wireless Sensor Nodes (ISNs). .. Then, we need to consider the way of collecting from the ISNs. Accordingly, we utilize a Patrol Node (PN) that moves around ISNs, and collects sensed data from ISNs. The ISN stores the sensed data until the time PN comes back. However, because the communication time to the PN depends on the speed of the PN, ISNs can not necessarily transmit all the maintained sensed data to the PN. Therefore, we suggest that the ISN should send adaptive data according to the speed of PN. We propose a technique for transmitting adaptive data depending on the movement of the PN. In addition, we have implemented a prototype of our proposal and verified the effectiveness of our proposed system. Finally, we show that our system improves the performance of the sensor network.

Analysis of fine-grained urban temperature collected with a sensor network

Temperature in a metropolitan area exhibits a complicated tendency. Rather than geographical closeness, structures of a group of buildings and streets can affect changes in temperature. To identify the tendency of fine-grained distribution of temperature, we installed a densely-distributed sensor network called UScan. In this paper we describe a system of UScan and effective placement of sensors based on our experiment in downtown Tokyo. We also propose a clustering method to analyze the correlation between the tendency of temperature and the environmental factors.

A Sensed-Point-Oriented Geographic Routing for Camera Networks

Camera networks have been paid much attention in sensor networks since those network are useful to visualize a phenomenon sensed by other sensors for temperature, humidity, and light. When a user selects a point of an area deployed cameras in an application, a geographic routing is best used as a routing of the camera network. In conventional geographic routing, the destination of a message should be the location of a node. However, this is not suitable for sensors that cover a wide or directed sensing area such as cameras. To cope with this problem, we propose a modified geographic routing scheme called SenriGan. SenriGan accommodates specifying a sensed point as a destination instead of using a location of a node. In this demonstration, we show a prototype system of SenriGan.

SenriGan: A Sensed-Point-Directed Geographic Routing for Sensor Networks

Geographic routing has been paid much attention in query-based sensor networks since sensed data inherently pertain to the location of the data. In conventional geographic routing, the destination of a message should be the location of a node. However, this is not suitable for sensors that cover a wide or directed sensing area such as cameras. To cope with this problem, we propose a modified geographic routing scheme called SenriGan. SenriGan accommodates specifying a sensed point as a destination instead of using a location of a node. In this paper, we describe our proposed system architecture using image sensor networks and an implementation of its prototype.