HiFleet receives BV VeriSTAR Green data-interface attestation
Bureau Veritas issued an attestation for the data interface between BV VeriSTAR Green and HiFleet’s vessel energy-efficiency management system.
This page summarises publicly available third-party collaborations, cases, coverage and research citations related to HiFleet. Descriptions of HiFleet products, data and relationships follow the original third-party pages. Listing does not mean those organisations endorse all HiFleet products or views.
Related: About HiFleet · Data methodology
Bureau Veritas issued an attestation for the data interface between BV VeriSTAR Green and HiFleet’s vessel energy-efficiency management system.
HiFleet is listed on the public page of the BIMCO Technology Partnership Programme.
A public report by Shanghai financial authorities states that China Everbright Bank Shanghai Branch worked with the Shanghai Data Exchange and Shanghai Maili Marine Technology Co., Ltd. on China’s first DCB-based data-asset credit enhancement financing, with a credit line of RMB 5 million. The public information refers to a “latest vessel AIS query” data asset, listing on the Shanghai Data Exchange, and compliance and quality assessment.
In 2025, the project “Shipping big-data-driven intelligent vessel energy-efficiency and low-carbon navigation service platform”, submitted by Shanghai Maili Marine Technology Co., Ltd., was included in the published selection results for Shanghai’s modern shipping-service innovation potential projects.
Shanghai Maili Marine Technology Co., Ltd. participated as one of the main completing organisations in the project “Key technologies for electronic chart production and navigational support applications for China’s coastal and important marine areas”, which received the Second Prize of the 2019 Surveying & Mapping Science and Technology Progress Award (project no. 2019-01-02-34).
Shanghai Maili Marine Technology Co., Ltd. participated as one of the main completing organisations in the project “Key technologies and applications for lean control of ship navigation risk based on holographic profiling of tidal ports”, which was listed among Second Prize winners of the 2023 China Institute of Navigation Science and Technology Progress Award.
Public coverage mentions a seminar on maritime digital talent development and innovation.
Tecway Europe describes HiFleet as a maritime big-data and fleet-management platform, and refers to onboard DTU, AIS position updates, route optimisation, CII and vessel performance monitoring.
nautical.my describes HiFleet’s AIS positions, weather, electronic charts, ship particulars, DTU, CCTV monitoring and route-optimisation services.
In a report on Shanghai Port operations, Shanghai Observer cited HiFleet data to analyse Yangtze estuary channel traffic, anchorage vessel counts and average waiting time at anchor.
In coverage of a missing vessel, 5iShipping cited AIS data provided by HiFleet to describe when the track stopped updating and the last known position.
Selected maritime, shipping and navigation studies have used or cited AIS data, maps, figures or publicly available platform information from HiFleet. Each entry below describes the form of use stated in the paper and links to the publisher or an open-access record. Listing is not an academic endorsement of HiFleet.
Yinxia Cao, Haoyu Wang, Fenzhen Su, Dongjie Fu, Fengqin Yan, Xiaorun Hong, Wenxing He, Nan Xu, Yifu Ou, Chunpeng Chen · The Innovation · 2026 · DOI: 10.1016/j.xinn.2026.101367
According to the publicly available abstract, the raw dataset was obtained from the HiFleet platform and contains 154,050,657 records. The study integrates satellite radar and AIS data to assess shipping-traffic changes through the Strait of Hormuz.
Hailin Zheng, Qinyou Hu, Chun Yang, Qiang Mei, Peng Wang, Kelong Li · Journal of Marine Science and Engineering · 2023 · DOI: 10.3390/jmse11081516
This study used AIS data provided by HiFleet to analyse trajectory jumps and identify suspected spoofing vessels through trajectory segmentation and an isolation forest method. The reported sample comprised 20 container ships and 52,538 AIS records.
Zhihuan Wang, Christophe Claramunt, Yinhai Wang · Sensors · 2019 · DOI: 10.3390/s19153363
The paper states that the global AIS database and ship-characteristic database were mainly provided by www.hifleet.com, and uses 2015 container-ship trajectories to extract multi-level global shipping networks.
Jianwen Ma, Qinyou Hu, Tian Liu, Zhaoxin Zhu, Yue Zhou · ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering · 2024 · DOI: 10.1061/AJRUA6.RUENG-1190
This study applies AIS data and an Ising model to analyse ship-collision risk in Qingdao Port waters. A HiFleet map was reproduced in the paper with permission. This entry confirms a map citation only; it does not by itself prove that all AIS data used in the paper came from HiFleet.
Miao Gao, Jinqiang Bi, Zhen Kang, Shuai Chen, Peiru Shi, Xi Zeng, Anmin Zhang · The Journal of Navigation · 2025 · DOI: 10.1017/S0373463325000050
This study develops a ship navigable route framework from AIS big data and cites a HiFleet figure and publicly available platform information in describing the accumulation and application of vessel-trajectory data. Current evidence is not sufficient to show that all research data were provided by HiFleet.
Haoyang Wu, Zishuo Huang, Qinyou Hu, Xin Ran, Qiang Mei · IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · 2024 · DOI: 10.1109/jstars.2024.3470903
A public figure caption indicates that GeoAISNet correction performance in the South China Sea was shown or tested on the HiFleet platform. This entry is listed as platform testing and does not by itself prove that all source AIS data came from HiFleet.
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