Project

Transportation Bigdata

As increasing the variety of transportation, users expects the system to provide a wide variety of choice according to their circumstance. Nowadays, though big railway companies could provide real time information of their vehicles, most of public transportation services such as buses and taxies, and ride share vehicles couldn't cooperate each other and provide sufficient information to users. MaaS (Mobility as a Service) is one of the expected solution.

Issues

We collaborate with Kobe Minato Kanko Bus Inc. which operates route buses in Kobe city every day. The company provides us realtime sensor data (eg. GPS, Car speed, Engine speed, Temperature, Humidity, Air pressure, ...) from the real operating buses every 0.5 second. We analyze them and feedback the results to the company for enhancing the operation management efficiency and usability of passengers.

Main topics are as follows. We achieve higher performance of inferring bus operation states and automatic counting of passenger of getting on/off the buses.

  • Analyzing sensor data which is installed in the buses
  • V2X (Vehicle-to-everything) communication technology
  • Developing yet another sensor
  • Developing bigdata computing systems
  • Field study of edge computing

Publication

  • Takumi Niwa, Ismail Arai, Arata Endo, Masatoshi Kakiuchi, Kazutoshi Fujikawa, “Improving Bus Arrival Time Prediction Accurancy with Daily Periodic Based Transportation Data Imputation,” 2023 International Conference on Smart Mobility (SM), pp.126--131, Thuwal, Saudi Arabia, March, 2023, doi: 10.1109/SM57895.2023.10112252. [IEEE Xplore]
  • Takumi Fukuda, Ismail Arai, Arata Endo, Masatoshi Kakiuchi, Kazutoshi Fujikawa, “Benchmark of Deep Learning Visual and Far-Infrared Videos Toward Weather-tolerant Pedestrian Traffic Monitoring,” 2023 International Conference on Smart Mobility (SM), pp.45--50, Thuwal, Saudi Arabia, March, 2023, doi: 10.1109/SM57895.2023.10112301. [IEEE Xplore] (Best paper award)
  • Tatsuya Yamamura, Ismail Arai, Masatoshi Kakiuchi, Arata Endo, Kazutoshi Fujikawa, “Bus Ridership Prediction with Time Section, Weather, and Ridership Trend Aware Multiple LSTM,” 2023 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), pp.484--489, March, 2023.
  • Masato Kawashima, Ismail Arai, Arata Endo, Masatoshi Kakiuchi, Kazutoshi Fujikawa, “Origin Destination Estimation Carrying over Rolling Proximity Identifiers with RSSI,” 2022 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT), pp.7--12, Alexandria, Egypt, 2022, doi: 10.1109/GCAIoT57150.2022.10019176. [IEEE Xplore]
  • Ahmed Elnoshokaty, Ismail Arai, Samy El-Tawab, Ahmad Salman, “Transit System Prediction for Real-time Weather Conditions: Fleet Management and Weather-related Ridership,” 2022 International Conference on Smart Mobility (SM), pp.14--20, New Alamein, Egypt, March, 2022, doi: 10.1109/SM55505.2022.9758295. [IEEE Xplore]
  • Ismail Arai, Ahmad Elnoshokaty, Samy El-Tawab, Ahmad Salman, “The Effect of COVID-19 on the Transit System in Two Regions: Japan and USA,” 2021 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT), pp.1--6, Dubai, United Arab Emirates, 2021, doi: 10.1109/GCAIoT53516.2021.9693002. [IEEE Xplore]
  • Ismail Arai, Ahmed Elnoshokaty, Samy El-Tawab, “Leveraging IoT and Weather Conditions to Estimate the Riders Waiting for the Bus Transit on Campus,” 2021 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), pp.552--557, March, 2021, doi: 10.1109/PerComWorkshops51409.2021.9431016. [IEEE Xplore]
  • Euclides Chauque, Ismail Arai, Kazutoshi Fujikawa, “Reducing Tail Latency In Cassandra Cluster Using Regression Based Replica Selection Algorithm,” 2020 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT), pp.1--7, Dubai, United Arab Emirates, 2020, doi: 10.1109/GCAIoT51063.2020.9345823. [IEEE Xplore]
  • Atsuto Ishinaga, Ismail Arai, Kazutoshi Fujikawa, “Route-Bus Driver Evaluation System Using Digital Tachograph Data and Static Route Features,” 2020 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT), Poster, Dubai, United Arab Emirates, 2020.
  • Toyokazu Akiyama, Ismail Arai, Hiroshi Yamamoto, “[Poster Presentation] Research and development of a safe bus driving support system considering passenger discomfort,” IEICE Tech. Rep., Vol. 120, No. 177, IA2020-12, p.32, Online, October, 2020. [IEICE DL]
  • Ismail Arai, Masahiro Kametani, Norihiko Honda, and Toyokazu Akiyama, “DOCOR: Sensing Everything From Route Buses,” 2020 IEEE 6th World Forum on Internet of Things (WF-IoT), pp.1--2, New Oleans, LA, USA, June, 2020, doi: 10.1109/WF-IoT48130.2020.9221027. [IEEE Xplore]
  • Samy El-Tawab, Ismail Arai, Ahmad Salman, and B. Brian Park, “A Framework for Transit Monitoring System Using IoT Technology: Two Case Studies,” 2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), pp.570--575, USA, March, 2020, doi: 10.1109/PerComWorkshops48775.2020.9156130. [IEEE Xplore]
  • Hayato Nakashima, Ismail Arai, Kazutoshi Fujikawa, “Passenger Counter Based on Random Forest Regressor Using Drive Recorder and Sensors in Buses,” 2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)), pp.561--566, Japan, Mar, 2019. [IEEE Xplore]
  • Hayato Nakashima, Ismail Arai, Kazutoshi Fujikawa, “Proposal of a Method for Estimating the Number of Passengers with Using Drive Recorder and Sensors Equipped in Buses,” Proceedings of 2018 IEEE International Conference on Big Data, pp.5379--5381, U.S.A, December, 2018. [IEEE Xplore]
  • Hayato Nakashima, Ismail Arai, Kazutoshi Fujikawa, “Counting Passengers from Images of Drive Recorder Inside Buses by Using Background Subtraction and OpenPose,” Internet Conference 2018, Poster No.15, 2018年11月. [PDF]
  • Takuya Yonezawa, Ismail Arai, Toyokazu Akiyama, Kazutoshi Fujikawa, “Random Forest Based Bus Operation States Classification Using Vehicle Sensor Data,” 2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), pp.819--824, Greece, March, 2018. [IEEE Xplore]
  • Hayato Nakashima, Ismail Arai, Kazutoshi Fujikawa, “Proposal of Estimating Number of Passengers Using Images of Drive Recorder Inside Buses,” Student Workshop, MobiCASE 2018, Japan, March, 2018. [PDF]
  • Takuya Yonezawa, Ismail Arai, Toyokazu Akiyama, Kazutoshi Fujikawa, “Proposal of classification method of bus operation states using sensor data,” Proceedings of 2017 IEEE International Conference on Big Data, pp.4781--4783, U.S.A, December, 2017. [IEEE Xplore]