Step up the distribution of sanitary equipment
By IVADO Labs | Published on February 17, 2022
Problem and objectives
Problem
- Transport of sanitary equipment in search of optimization in pandemic conditions.
Objectives
- Identify containers carrying medical equipment;
- Optimize the handling of goods;
- Develop predictive tools to support decision making.
Proposed solution
Solution
The mission of IVADO Labs is to help Québec companies integrate artificial intelligence solutions into their operations. The company acts as an investment and consulting firm.
The COVID-19 health crisis took all countries by surprise and forced port authorities to rethink their priorities in handling goods. Medical devices had to be identified and then shipped as quickly as possible to hospitals and other health care institutions. It was in this context that Port of Montréal authorities contracted IVADO Labs to create two modules to:
- More quickly identify containers carrying medical equipment;
- Step up the transfer of these goods from the Port of Montréal (e.g. masks, disinfectants).
Principle
IVADO Labs has developed two solutions that allow Port of Montréal authorities to improve their decision-making related to container processing.
- The first tool identifies the goods in containers arriving at the port using natural language processing techniques.
- The second module optimizes freight transportation management once it has been identified.
The combination of the two modules allows port authorities to ship more equipment faster, which is a significant advantage in a health crisis.
User experience
Using the solutions created by IVADO Labs, Port of Montréal authorities and their partners obtain more information about goods arriving by container. The algorithm also incorporates a predictive and optimization facet that allow officials to better process the movement of the goods. Pooling the elements that were developed enables the various Port of Montréal stakeholders to be supported in their decision-making.
Role of AI
In developing the algorithm, IVADO Labs used a variety of techniques, including:
- Machine learning;
- Gradient boosting;
- Predictive analysis
- Linear integer optimization. Automatic natural language processing;
- Classification;
- Regression;
- Etc.
Impacts
Main outcomes
Impact on the Port of Montréal:
- 50% reduction in container shipping time;
- Increase in potential prediction period from 1 to 16 days;
- Increase in the number of containers that can be shipped from 5% to 10%;
- International recognition for its use of AI.
Impact on IVADO Labs:
- Development of expertise in freight transportation and supply chains.
Impact on the Québec health system:
- Medical equipment shipped faster to hospitals during the COVID-19 pandemic.
Generation and dissemination of new knowledge
- Sharing of knowledge with Port of Montréal authorities and its partners throughout the project
Challenges takled
- Adapting to the complexity of port operations;
- Inclusion of a significant number of stakeholders such as shipping lines and railways;
- Pooling of data received from various independent systems used in the management of port operations;
- Management of the privacy of the collected data.
Conditions for success
Team mobilised
The IVADO Labs’ AI project team consisted of :
- Data analysts;
- Solution architects;
- Data scientists;
- Data engineers;
- Software developers;
- UI/UX designers;
- Project manager.
Collaborations
The following collaborations contributed to the success of the project:
- Outstanding involvement on the part of Port of Montréal authorities and partners;
- Support from Port of Montréal management;
- Funding received from Scale AI;
IVADO Labs collaborated for the project with players such as:
- CargoM;
- Canadian National;
- Canadian Pacific;
- Scale AI
- Several shipping lines.
Project stages
Evaluation of objectives and methodological planning;
Algorithm and infrastructure development;
Implementation of the solution in the Port of Montréal’s system.