Environmental Impact

A simulation model to calculate carbon footprint

Research on how using the significant quantities of data extracted from our real-time tracking and engine management information we can model, analyze and report on the environmental footprint of transport fleets and drive change through awareness, possible route and mileage savings and critically establish environmental impact as one of the criteria driving route optimization.

Large Scale Route Optimisation

Creation of multi-route optimization algorithms to develop an application to reduce considerably the processing and memory requirements

Research and development on how we can port the complex mathematical models that we have previously developed on our backend servers to run efficiently on client and handheld machines in order to accommodate dynamic solutions.

Green Wave

Creation of a simulation using a Location Based System (LBS), to enable emergency vehicles to arrive to their destination. The aim was to cut down response times for emergency services.

Research and investigation on how we can provide a “green wave” to cut down response times for emergency services.

Galileo Satellite Constellation

Research on Galileo Satellite - on coverage, continuity, precision and accuracy and availability.

Research and validate the anticipated Galileo satellite constellation and to investigate how we can exploit the enhancements it promises to bring to location accuracy and the additional services it will eventually provide on top of standard GPS functionality.

Recent Works

Hybrid Dynamic
Route Optimisation

Creation of a simulation model comprising elements such as Traffic volumes and Performance, Performance improvement by driving intelligent routes with decreased route mileages, Reduction of fuel costs and decreased in vehicle emissions.

Research on how to develop a hybrid dynamic route optimisation and navigation tool taking into consideration the following: Time window constraints, Vehicle volume and payload constraints, past knowledge of actual delivery point locations, actual real-time variations (delays/ gains) in route navigation.

  1. Time window constraints
  2. Vehicle volume and payload constraints
  3. Past knowledge of actual delivery point locations
  4. Actual historical road speeds and drive times achievable depending on time of day
  5. Actual real-time variations (delays/ gains) in route navigation
  6. Traffic volumes and traffic Performance
  7. Driver-centric features including driver safety
  8. Performance improvement by driving intelligent routes with decreased rout mileages
  9. Reduction of fuel costs and decreased in vehicle emissions
  10. Smaller carbon footprint

LOQUS Business Intelligence

By adhering to the principles of progressive enhancement and addressing constraints first, we're laying a future-friendly foundation that gives our solutions a better chance of working in future browsers and environments.

Research and Innovation

LOQUS places great emphasis on research and innovation, over the past years LOQUS participated in R&D in relation to carbon footprint emission reduction, waste minimization and air pollution reduction aimed to improve the environment and increase financial savings.

Research and Development

LOQUS has a well mapped out strategy of continuous product development which is driven by a research program to continue investigating techniques to help it maintain its position as one of the leading developers of logistics solutions for marine and land based fleets.

  • horizon 2020
  • fp7
  • eu