With this in view, launching Decision Support System for Urban Administration
Backed by technological intervention through artificial intelligence and machine learning enabling them to take effective and informed decision making
Components of city administration
Outputs to be generated in the form of
SIMULATIONS
PREDICTIONS
IDENTIFICATION
REAL TIME ACTIONS
ULB under Smart City Mission
With the help of integrated command and control centre (ICCC), a large chunk of data is being collected at a single place (ICCC) with regards to civic requirements on a daily level. With the help of smart analytics based on intelligent tools and techniques, a layer of DSS on top of the existing ICCC could aid in achieving the objective.
ULB not under Smart City Mission
Majority of the departments work in silos; therefore, data collection is the first step. Despite, a large chunk of repository is maintained within the database of ULBs. Thus, a DSS dashboard for the same could be developed.
Decision Support System (COVID 19) A data backed hyperlocal DSS for effective resource utilisation and policy making decisions.
ECONOMIC LAYER
To determine the impact of COVID on different sectors of the industries, help government take decision on the incentive announcements, employment tracking.
SOCIAL LAYER
To determine the psychological impact of lockdown, disruption of essential supplies as well as with the crime rate changes.
SPREAD LAYER
To predict the spread of COVID based on SEIRD model as well as allow government to take decision based on the contingency and threshold allowed.
RECOMMENDATION LAYER
With the help of number of domain experts and the result derived from the model, we catered to provide certain policy recommendations to the authorities.