Ms. Eiko Saito, Researcher of Knowledge System Research Group, Knowledge and Data System Department, received the Freshman Presentation Award from Japan Institute of Navigation at the 137th annual autumn meeting of the Institute. The awarding ceremony was held on Friday, October 20, 2017.
"On the estimation of course and speed required for collision avoidance of small crafts by using position data obtained by smartphones"
Authors: Eiko Saito, Junji Fukudo, Makiko Minami, Masayoshi Numano
Although the number of marine accidents has decreased, there have been still over 2,000 ships involved in accidents every year for the last 10 years in Japan. More than 70% of them were small crafts such as pleasure boats and fishing boats.
As smartphones become small and cost effective, and have many “smart” functions such as position acquisition and internet connection function, they came to be used as a collision avoidance support device for small crafts. However, if the device did not perform properly because of its insufficient performance, it would lead the users to a collision accident.
To confirm the basic performance of smartphone’s communication and position acquisition system which is used for collision avoidance support, a series of actual sea experiments were carried out using two small crafts. Each craft had a smartphone with an application for collision avoidance support, which acquires own position data, uploads the position data to the internet data server and downloads other craft’s data and collision alarm from the server. Various data handled by the application were recorded with time stamps to the phone and the server and analysed to investigate communication and data quality (e.g. communication delay, position, course and speed accuracy), as well as whether they were sufficient for collision avoidance purpose. We have also proposed a procedure for estimating course and speed of the craft based on the recorded position data. The results indicate that a smartphone based system, by using the proposed procedure, can provide effective alerts for collision avoidance.