Sustainable Facility & Estate Intelligence

Outcomes - A single view of a facility's sustainability, safety and operations data instead of eleven registers and one very tired caretaker - Anomalies detected and short-term changes forecast before they become complaints - Plain-language recommendations an administrator can act on the same morning - Role-based views for administrators, operations teams and sustainability officers - A sustainability scorecard the institution can actually publish Overview The dashboard should ingest open, synthetic or sensor-style data, visualise trends, detect anomalies, forecast short-term changes and generate plain-language recommendations for administrators. Modules may include air-quality monitoring, waste-bin overflow prediction, energy-usage optimisation, water-use alerts, traffic or parking hotspot analysis, equipment utilisation, safety incident trend monitoring and sustainability scorecards. A strong prototype combines data visualisation with AI-generated insight, scenario simulation and action recommendations — changing collection routes, sending advisories, adjusting energy schedules, identifying pollution hotspots, optimising facility maintenance, or prioritising inspection zones. The Story The estate officer has a spreadsheet, a WhatsApp group, and a strong feeling that something is wrong. The electricity bill went up 18% and nobody knows why. Bin number 7 near the canteen overflows every Wednesday, reliably, like a festival. The water tank ran dry twice last month and both times somebody blamed the pump. All of this data exists. None of it is in the same room. Put it in the same room and let it talk.

• A working dashboard ingesting at least three data streams for a clearly declared facility type, with data sources and assumptions documented
• At least two AI/ML components — a forecast and an anomaly detector — with performance shown honestly, failures included
• An insight-and-recommendation layer producing plain-language actions tied to specific, named interventions
• A scenario simulation ("what if collection shifts to Tuesday", "what if HVAC runs an hour less") with projected impact
• Role-based views plus a configuration path showing how the same build serves a hospital and an industrial estate

• Sustainability and operations relevance across Indian facilities — 20%
• Data engineering and visualisation — 20%
• AI/ML modelling, forecasting or anomaly detection — 20%
• Actionability of recommendations — 15%
• Usability for administrators, explainability of assumptions, and demo quality — 25%