Event Data.Gov.in

Following are probable Problem Statements for Smart Cities Mission

Sector: Education
Problem Statement:To setup adaptive learning management system for teachers and municipal schools.
Different students have different learning needs. Municipal Schools are introducing Information and Communication Technologies (ICT) for effective teaching and coaching purpose. Adaptive learning makes this possible by using student data. Adaptive learning uses the data learners generate to:
• Produce personalized learning plans based on individual capabilities
• Recommend methodologies to teachers that suit their aptitudes
• Monitor and follow up on progress
Adaptive learning uses learning objectives, their learning history and previous learning content to develop personalized learning plan for individual students. Smart Cities aims to develop Adaptive learning solutions for municipal schools to allow students to teachers to enhance the learning experience using Open technologies. Smart Cities aims to scale the solution to 4000 cities which could be powered by open content platform where experts could contribute and evaluate the content. Solution has to be interoperable, open and scalable.

Sector: City Economy
Problem Statement: AI -based application for GDP Assessment and analysis of cities.
Smart Cities needs various data points to asses the economic health or growth over the period. Smart Cities aims to set up open configurable mobile compatible platform to promote crowd sourcing to collect various data points from citizens and communities. Platform shall be designed using open source technologies to facilitate various services namely Location discovery, Price monitoring, asset inspections, movement patterns, logistic monitoring, sentiments analysis and surveys. Platform shall allow end users to configure various features to collect, process and aggregate data to generate economic insights at the city level ex: cost of living, spending propensity, tax potential, market price etc. Smart Cities Mission aims to scale the solution to 500 cities.

Sector: Mobility
Problem Statement: Design open source solution using AI and Machine Learning to help city bus authorities/undertakings to schedule city buses on different routes using passenger mobility data.
To promote the usage of public transport among the masses it is important to increase the reliability and improve the user experience of the commuters. Problem arises due to poor allocation of bus routes in absence of commuter data, traffic congestion, bus break down, poor roads etc. which either leads to unreliable bus timings, over or underutilized passenger loads. Smart Cities aims to use AI to deliver better, reliable and precise real time information to commuters and officials by using commuter (anonymized) movements data.

Sector: Solid Waste Management
Problem Statement: Smart Cities Mission aims to develop an effective system in a smart city to automate sanitary workers daily attendance to avoid fake entry/ proxy. The system to keep track of all entries/areas/unauthorized access etc. to maintain the audit trail and help in improving the efficiency and productivity of people and system.

Sector: Sanitation
Problem Statement: To develop an Artificial intelligence /machine learning based model of validation of the functional /non-functional Toilets in the cities, through citizen engagement.

Sector: Water and Waste Water
Problem Statement: To develop an AI based model to improve understanding of the ground water system in the cities wrt porous, fractured, contaminated formations near water intrusion area & sewage effluents. The integrated model to have various thematic maps and their spatial analysis of apparent resistivity, lineament frequency, drainage frequency, geomorphology, soil/overburden thickness and aquifer thickness of ground water importance.