Period: 2021 – 2022
AI FERODATA - project no. 2020/548467, funded through the Innovation Norway program, Norway Grants 2014 - 2021, SME’s Growth Romania.
The total value of the project was 559,055 Euros, of which 363,500 Euros were non- refundable financing. The activities took place over a duration of 16 months, with 24 experts from GREENSOFT being part of the team.
Description: The technical solution developed within the project is an intelligent, efficient, and state-of-the-art management assistant for the following objectives: locomotive data management and correlated parameter analysis; automatic tracking of transport relationships; calculation of travel times and station times; automatic calculation of electric and diesel fuel consumption in transport and electricity distribution zones using GIS functions; real-time comparison of actual consumption with consumption norms and generation of instant consumption alerts in case of overconsumption; identification of potential fuel theft through locomotive parameter correlation analysis; dispatcher alerting in case of communication loss; obtaining traction fleet performance reports and locomotive worker hours.
AI FERODATA - project no. 2020/548467, funded through the Innovation Norway program, Norway Grants 2014 - 2021, SME’s Growth Romania.
The total value of the project was 559,055 Euros, of which 363,500 Euros were non- refundable financing. The activities took place over a duration of 16 months, with 24 experts from GREENSOFT being part of the team.
Description: The technical solution developed within the project is an intelligent, efficient, and state-of-the-art management assistant for the following objectives: locomotive data management and correlated parameter analysis; automatic tracking of transport relationships; calculation of travel times and station times; automatic calculation of electric and diesel fuel consumption in transport and electricity distribution zones using GIS functions; real-time comparison of actual consumption with consumption norms and generation of instant consumption alerts in case of overconsumption; identification of potential fuel theft through locomotive parameter correlation analysis; dispatcher alerting in case of communication loss; obtaining traction fleet performance reports and locomotive worker hours.