Application of Data to Unlock Cities' Growth

Cities are engines of growth, and it has been widely acknowledged that 'data is the new oil', essential to sustainably develop and efficiently manage cities. Urban data, especially spatially and temporally disaggregated, is a key to tracking the liveability and sustainability challenges faced by cities. The application of data science and technology can enable effective structuring of various data sets to tackle such urban challenges. The data thus captured can be used for finding solutions to urban challenges in a cost and time efficient manner.

Community engagement is at the centre of this spatial data platform

Can we harness the power of technology and community to resolve these challenges? How would such a system shape up?

 

These are the questions at the heart of the Spatial Data System for the Inclusive Cities Agenda in India project, being implemented by Information Technology for Change (ITfC), AVAS and the Center for Study of Science, Technology and Policy (CSTEP).

 

Examining Sustainable Pathways for India’s Development Aspirations

Energy-environment-economy models (commonly known as E3) are often used to explore greenhouse gas mitigation policies. One such class of models is the computable general equilibrium (CGE) model. The large-scale, comprehensive analytical framework is widely used to make long-term projections on issues related to growth, jobs, investments and emissions. More importantly, it can be used to assess the economy-wide consequences of changes in policies.

Reliable Data: A Prerequisite for Effective Energy Auditing

AT&C loss reduction is one of the key elements in UDAY’s strategy for making DISCOMs financially viable. Energy auditing forms an integral part of AT&C loss reduction as it helps with the identification of areas plagued with leakage and wastage of electricity in a DISCOM’s jurisdiction. The prerequisite for an effective energy audit is the availability of accurate and reliable data for energy input at the feeder and energy received at the consumer end.

Bolstering Rooftop Photovoltaic Uptake in Karnataka

The Center for Study of Science, Technology and Policy (CSTEP) entered into a tripartite agreement with Bangalore Electricity Supply Company (BESCOM) and Karnataka Renewable Energy Development Limited (KREDL) to promote RTPV in Bengaluru. CSTEP is using Light Detection and Ranging (LiDAR) technology to obtain aerial images of the city. A helicopter, coupled with a LiDAR system, flew over the city to map the RTPV potential. The flights covered almost 1,100 sq. km and captured high-resolution images, including topography, buildings and trees.

India’s Climate Policy: A Formidable Conundrum

Many observers agree that India's climate targets and the recent policy thrust are balanced and rightly safeguard India’s right to develop. The NDC itself remained anchored to principles of Common But Differentiated Responsibility (CBDR) and is in line with India’s capabilities. So far, India has not yet undergone a high fossil intensive growth — its emissions intensity of GDP and per capita emissions are quite low. However, going forward, all eyes are on us. How will India marry its growth ambition with our goal to remain 'sustainable'?

No Child's Play!

The AI and Digital Lab at CSTEP has designed SNEHA, an app that can detect and help tackle malnutrition and growth-related health problems in children and new mothers. A part of the solution, Sneha Child Monitor was provided to Ramnagara district officials for a comprehensive survey on the nutritional status of children in the district. The tool allows easy registration of children, and records their growth measurements.

Quantifying pollution is the starting point for change

Dr Sarath Guttikunda is the founder of UrbanEmissions.Info (UEinfo, India). His main research interest lies in urban emissions and finding ways to bridge the gap between science, policy, and public awareness. In this interview, he speaks about the APnA city program and his work in dispersion modelling to understand spatial distribution of pollutants.