The Internet of Things (IoT), which extracts useful information for people’s daily lives by collecting and analyzing sensing data measured by sensors installed in various locations and smartphones owned by various people, is attracting attention. Moreover, MCS (mobile crowd sensing), which utilizes smartphones as sensing devices to acquire various environmental data such as temperature and altitude, is expected to become a low-cost measurement platform to collect environmental data over a wide area.
Therefore, we are researching technologies to promote the use of IoT and MCS, focusing on the following themes.
Detection System for Vermin Using Multi-Stage Sensors
In mountainous areas where it is difficult to secure a power source, damage from animals (vermin) that cause damage to crops has become a problem. To mitigate the damage from pests, an autonomous recording unit (ARU) has been used to monitor wildlife by voice. However, because the ARU is operated intermittently to reduce power consumption, it is difficult to capture events when the ARU is in standby mode.
To solve this problem, we are working on a wildlife monitoring system in which only some of the sensor nodes located in the target area are activated, and when the activated sensor node detects a bird or animal, it activates the surrounding sensors in standby mode, aiming to improve event capture while reducing power consumption.
Rescue Techniques at Disasters Using Drone
During disasters such as earthquakes and typhoons, it is difficult to use mobile devices due to expected damage to communication infrastructure and power outages. Therefore, it is expected that drones, which can fly autonomously and transport supplies, will be used to search and rescue victims. However, in order to effectively use a limited number of drones to quickly find victims and carry out rescue activities, it is important to select and set appropriate travel routes for the drones.
To this end, our laboratory is working on technology to optimally design drone travel routes to minimize the time required to rescue victims.
Techniques Sharing Information at Disasters Using DTN
When a disaster strikes, information on evacuation centers and evacuation routes is essential for victims to evacuate safely and quickly. Although the collection of route breakdowns is necessary to propose appropriate evacuation routes, the communication infrastructure will be unusable in the event of a large-scale disaster.
To solve this problem, it is effective to collect information on route failures between mobile terminals owned by evacuees using a Delay Tolerant Network (DTN) without using communication infrastructure and propose evacuation routes using this information.
To this end, we are working on a research project to determine the accessibility of faulty points on the evacuation route for each evacuee attribute, and to seek and present evacuation routes for each evacuee attribute.
Prevention Techniques for Data Poisoning Attack in Crowdsensing
Crowdsensing, which utilizes mobile devices such as smartphones as sensor devices to infer the true values of various environmental data, is attracting attention. However, since the true values are estimated from the reported values of an unspecified number of users, the problem of data poisoning attacks has been pointed out, where attackers intentionally report false data, to degrade the accuracy of the true value estimation.
Therefore, our laboratory is working on schemes of data poisoning attack in crowdsensing and defense techniques agaist them.
Co-Created Urban Digital Twin Business Model
A co-creation urban digital twin that predicts the future state and conditions of the society in which people live by collecting a wide variety of real-world data from “city dwellers” and simulating them in cyberspace is attracting attention. The key to realize a sustainable co-creation urban digital twin is how to provide incentives to residents to provide data.
Therefore, this laboratory is engaged in research to verify what kind of business model is desirable by using evolutionary game theory, which can analyze the dynamic relationships among stakeholders using differential equations.