8.Conclusion

Future Work

Dataset still has some outliers in location related features. This issue will be resolved in the future version
I performed clustering on incident duration and agency engagement grouped by cities. So, different groups of data could be explored for clustering as well as other clustering techniques
Better result could be achieved by performing dimensionality reduction for clustering or hyperparameter tuning
Detailed time series & geospatial analysis on the dataset
The impact of/correlations with the lockdown and other Covid-19-driven policy actions/agency activities in different states in 2020
Detailed investigation on the possible correlation/inference with the incidents and local infrastructure

Demographic data would be valuabe to do research on users to find more insights and their association with emergencies
A glossary / clear explanation of all emegercy codes (description) would be valuable to sort out incidents
Research work on PulsePoint can be found here - https://www.pulsepoint.org/research-studies