Make Paris apocalypse-proof
Paris can be a frightening and unpredictable place— the flooding of the Seine, uncontrollable fires, epidemics, terrorist attacks, and the roving packs of wolves that roam the streets.
Okay, so fortunately we don’t have wolves (yet), but you have to admit our systems still have a lot of vulnerabilities. Fortunately, we now have the ability to use subjective analyses to trend, forecast, predict and project conditions that create risk for Paris and its many inhabitants.
In a city covered by location-sensing satellites, beacons, cellphones and Open Street Map, why shouldn’t we be prepared? Tools like current statistics, predictive modeling and forecasting, process analysis and organizational intelligence are just the first steps to preventing a dystopian situation against the scenic backdrop of the Seine.
How might we leverage new technologies and data sources to keep Parisians safer?
Number of reserved slots: 2
Challenge type: Open
Tracks: Data science, Mapping
Keywords: process analysis, predictivemodeling, disasterpreparedness, riskreduction
- 4G antennas respecting alert standards
- Reuse of AIS/ADSB/-RDS/TNT (See Challenge: Prototype Open Radio Receiver)
- Beacons to detect floods, violent winds, earthquakes, etc.
- Use of distributed network protocols (batman, olsr, bmx, robin)
- Mesh Wifi in dense urban environments to deal with network overload: MCE (Mass Call Events)
Consult the full list here.
For Terrorism Risks:
For Environmental Risks:
For Epidemiological Risk:
- Water Quality : *caution, not machine-readable
- DAMIR health insurance expenses by territory
- OpenMedic with consumption by region
- Location of healthcare centers: Geolocation of healthcare and social service centers , Croix rouge
For fire hazards and accidents :
- Geolocation of fire stations in Paris and petite couronne
- Intervention statistics
- Database of bodily injuries