FindIT4all

Inspiration

The shortage in medical supplies during a pandemic crisis often leaves both frontline-healthcare workers and citizens unprotected. Covid19 has underscored that in these conditions, healthcare system's supply chain mechanisms are unable to provide effective solutions.
After the pandemic, demands for medical supplies will also shift to the local communities as the countries reopen from the lockdown. Personal medical protection production will be then in high demand for each citizen. The resources need to be highly distributed to guarantee that this demand is met.

We are an international team that took inspiration from what happened with the lack of the medical supplies so we put some of the knowledge form our involvement with EC projects related to supply chain optimization to solve this problem.

What it does

An online agent based ecosystem for supply chains focused on medical supplies.

Impact

Support the demand in more effective way in medical-services related supply-chain through digital collaboration platforms in order to avoid the lack of supplies as happened in Covid crisis, highly distribute the resources, and reduce the invisible cost without bypassing the third-party vendors.

Our Solution Approach:

A Web solution that to automatically address all the pain points on the supply chain:
1- Multiple agents for medical supplies to prevent shortages.
2- Matchmaking between suppliers and buyers so that all parties can navigate the supply-chain ecosystem easily.
3- Online bidding mechanisms between buyers and suppliers to simplify and automate negotiations.
4- Analytics for forecasting future demand, optimize planning and thus reduce the risk of shortages.　　

How I built it

The system is composed of 5 main components, User Dashboard, Agent ecosystem, Matchmaker, Online bidding mechanism, and Analytics platform.

User Dashboard is a Graphic User Interface that allows the actors to setup, modify, and manage the agents, start some bidding processes, and visualize the data analysis.

Agent ecosystem is an infrastructure that will enable the automated decision process and medical supplies allocation among the consumers. An agent will represent an actor in the ecosystem, collecting information that will come from the operating environment and the data analytics platform. A communication protocol will be established between agents to exchange information to support the negotiation/bidding process that will take place between them.

Matchmaker is a complete online semantic framework developed over Apache Jena and it is available through RESTful web services. It provides the mechanisms for requester and suppliers matching, and for real-time offers evaluation based on a set of user’s prioritized criteria (price, delivery time, payment and delivery methods, payment terms, certificates, rating etc.). This is the core component that contains the logic for suppliers discovery and matches the requesters.

Online bidding mechanism enables the negotiation between requester agents and supplier agents. when the Matchmaker receives a request from the requester agent and returns back all the matching supplier agents, The requester agent contacts the matched supplier agents in order to receive their offers, As soon as the requester receives the offers, it sends them to the Matchmaker for evaluation to get the best available offer. The matchmaker returns the result back to the requester. Finally, the requester agent notifies the suppliers if they are selected or not.

Analytic platform provides the forecasts to predict demands. There are two main types of forecasting methods:

Qualitative forecasting - based on experts opinions, customer surveys etc.
Quantitative forecasting – based on time series models that use historical data assuming the future will be like the past.

A Visual Analytics tool is introduced in order to deliver solutions related to quantitative forecasting methods:

Web-based tool supports different types of visualizations for both historical data and analytic methods output
Different type of analytics for the estimation of future quantities of a material/product based on history of orders for this material/product and future price of a material/product based on local or global historical data.

Challenges I ran into

Produce a valuable Business model.
Lack of abundant communication with the Medical domain experts.

Accomplishments that I'm proud of

The FindIT4All provides a user-friendly agent-based ecosystem that enables the agent's automated negotiation, the matchmaking, and analytic features of the platform, medical supplies could be allocated in a more efficient way, based also on the priority given by severity of different situations. This approach greatly prevents the shortage of medical resource during the crisis and distribute the medical supplies also among the local communities including pharmacies.

What I learned

Effective societal impact is definitely possible through high technologies and the joint force is the key to overcome the extremely difficult times.

What's next for FindIT4All

Further development of our solution and establish strategic partnerships with hospital supply chains and providers to further optimize the features.
Availability of the aforementioned supply chain’s data and concept in order to enhance analytic mechanisms and build a knowledge base that can be used by the agents for further reasoning and automation.
Funding support in order to proceed with the solution’s development and move from early prototypes to pilot application and possible product in later stages.
Support related to business planning etc.
Looking into partnering with solutions that allow us to integrate the transportation of the medical supplies, so that they can be optimally delivered to the buyer preferred stocking location.