Sensing Data Presentation System Technology
Many of the sensor network systems currently in use only have a function to unilaterally present acquired environmental information on a user’s terminal or simply accumulate it in a data logger or similar equipment. If the target range is narrow or its application is limited, even this functionality will be sufficient.
However, it may be difficult to quickly acquire desired monitoring information because, when continuously monitoring a large-scale disaster, the amount of data is too vast. Moreover, in order to grasp the situation of a disaster site and conduct rescue operations, utilization of various kinds of information equipment and network systems should be considered, and some of them are already in practical use. However, because each of these systems are unique in their development, they cannot be connected to one another. If two or more systems are introduced into a disaster site, extra time will be required to operate each system and it will be difficult to quickly acquire the information needed to conduct rescue operations. In view of the above, this research aims to create a function that, in addition to the sensing data, mashes up other useful information acquired from systems already existing in the network, without the need to modify each system, and present the results to the user. For data mashup, Google and other companies have provided APIs (Application Program Interfaces) to access their data and services, and anyone can construct new applications using the APIs. However, even if this service is used, not all network data can be mashed up. Moreover, by this method, the data mashup itself is executed on a dedicated server or terminal. The concept, therefore, is different from the aim of this research that the network router will perform data mashup in addition to data transfer.
Sensor Network Technology
Sensor network technology has also attracted attention as one of key technologies in today’s ubiquitous computing development and has resulted in active research and development being conducted in this field. Wireless sensor network (WSN) technology is especially suitable for environmental sensing conducted outdoors or on moving objects thanks to its ease of installation. Widespread applications are expected, including for use in disasters, crime prevention, environmental monitoring and other situations. Current WSN research centers on studies concerning network configuration methods (data link layer) and routing for data collection (network layer). In the data link layer, protocols such as LEACH  and S-MAC (Sensor MAC) , which stabilize the network while reducing battery consumption of each sensor node, are proposed. LEACH performs clustering in the network, and each node transfers data to the head of the cluster to which it belongs using TDMA (Time Division Multiple Access). By using TDMA, each node can go into sleep while it is not under assignment. However, the ratio of cluster heads to the total number of nodes should be known in advance; in fact, therefore, the ratio must be set suitable to its environment. This affects transfer efficiency and each node’s amount of battery consumption. S-MAC resembles the ad-hoc mode of a wireless LAN (IEEE802.11b). However, it differs in that it does not assume there is a beacon and that it considers multi-hop communication. For S-MAC, it is ideal that the schedules of all nodes synchronize. For the multi-hop, however, it takes time to give notice of synchronization time. Therefore, although there is a proposal for its remedy , it may still be difficult to apply S-MAC to our project. The network layer features the concept of data centric . In a sensor network, we do not want the information from a specific sensor node but instead only want a reply from the sensor node that holds the desired sensing data that suits our demand. To achieve a data centric solution, a different protocol from that of a conventional network using a node address or ID for communication is required. Directed Diffusion  realizes a data centric network through the flooding of the demand. This does not require any database (DB); but in a large-scale network, it is inevitable that the flooding will result in an increase in the amount of communication. As mentioned above, although conventional sensor network research includes flexibility to dynamically configure the network, it lacks a precondition to dynamically change the “roles” of sensor nodes; the goal of this research.
In the existing technique, furthermore, only academic examinations precede. Furthermore, with regards to existing methods, previously there have only been academic examinations. The majority has not gone beyond evaluation of simulations or small-scale indoor experiments conducted within an ideal environment. According to indoor and outdoor experiments that applicants have conducted with real sensor nodes, their radio wave propagation characteristics show significant variation in different environments along with considerable individual variability. These facts reveal that there are currently few existing techniques that can withstand use in real environmental conditions. Moreover, some sensors installed in WSNs monitoring disaster sites such as collapsed buildings or mudslides may become unusable. As a result, even if the network topology is dynamically configured or changed with the above-mentioned WSN communication protocols, the system itself may no longer acquire desired information. One of the goals of this research is to bring about a WSN that is capable of coping with these types of conditions. Furthermore, in order to obtain the data a user requires, we also aim to produce a function that dynamically changes the “role” of each sensor node in response to the user’s demand. Therefore, we prepare a “scenario description” which includes the “role” that each sensor node should play, along with the “role’s” trigger condition and operation sequence. This is transferred into each sensor node via wireless communication. We develop a mechanism to dynamically initiate each sensor’s “role” when it has satisfied the trigger condition as a result of environmental changes and/or a user demand. Reference  proposes a similar technology. However, its “scenario description” is limited and has not gone beyond evaluations based on simulations, leaving some doubts about its feasibility. This research aims to not only evaluate simulations, but also to create actual technology, including the development of sensor nodes, that is highly feasible.
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