Web-Based MVP: Intelligent Scheduling & Workload Prediction System for Medical Facility We are looking for an experienced freelancer or small development team to build a web-based MVP (Minimum Viable Product) of an intelligent scheduling and operational support system for a large medical network. The goal of this project is to develop a fully functional, browser-based demonstrator that operates on synthetic (simulated) data and showcases how the system would support scheduling, staffing decisions, and workload prediction in a real healthcare environment. This is not a production-level enterprise system — it is an MVP intended for demonstrations, stakeholder discussions, and preparation for a future pilot deployment. ⸻ Scope of the MVP (web-based application) The MVP should be delivered as a working web application, accessible online, with a simple UI and clear user flow. The system should include the following functional areas (in simplified form): ⸻ 1) Doctor / staff scheduling module • calendar / timetable view • staffing coverage by time slots / shifts • conflict detection, including: • understaffed time periods • scheduling conflicts / shift overlaps • exceeding working hour limits • manual editing / adjustments in the schedule ⸻ 2) Automatic suggestions & recommendations (rule-based / heuristic logic) The MVP should generate system suggestions such as: • recommended shift swaps • suggested reassignment of staff between units • flagged risk areas in the schedule Examples: • “Suggested shift swap between staff A and B” • “Recommended reassignment to cover high-priority workload” • “Minimum staffing not met — additional coverage required” AI / ML is not required at this stage — simple rule-based or heuristic logic is sufficient, as long as the system behavior is consistent and realistic. ⸻ 3) Basic workload prediction (simplified MVP version) A simplified workload indicator, such as: • low / medium / high workload risk Displayed in the schedule or dashboard, with a short explanation (e.g. “increased visit concentration between 10:00–12:00”). This may be implemented using: • moving averages, • simple statistical logic, • heuristic thresholds. ⸻ 4) “What-if” simulation panel Example scenarios to support: • absence of a staff member during selected hours • sudden increase in patient volume (e.g. +20%) The system should: • highlight risk zones, • show where coverage is insufficient, • present recommended adjustments or reallocations. ⸻ 5) Alerts & notifications (inside the web panel) Including (simplified): • missing coverage / staffing gaps • overtime / excessive workload indicators • conflicting shifts • high-risk workload periods ⸻ 6) Synthetic data — realistic & scenario-based The MVP should operate on synthetic test data, but the data must reflect realistic operational conditions, such as: • multiple departments / clinics • different shift patterns • night / weekend coverage • absence / unavailability cases • workload fluctuations Synthetic datasets may be prepared collaboratively. ⸻ Technical expectations Preferred (but not strictly required) approach: Backend / logic: • Python OR similar • rule-based / heuristic decision logic • optional solver frameworks (e.g. OR-Tools) Data layer: • simple database or structured data storage Frontend / delivery: • web-based dashboard / application • accessible from browser (no desktop installation) The final MVP must be delivered as: a working, online, web-based application ready for live demonstration (not just code or mock-ups). ⸻ Delivery expectations The deliverable should include: • functioning web application hosted in a demo environment • access for presentation and testing purposes • ability to run predefined demonstration scenarios • brief technical handover / instructions We value: • clean, pragmatic implementation, • focus on usability and clear scenario presentation, • experience with MVPs, PoC systems or decision-support tools.