CSTEP developed SANITECH, a decision-support tool, to facilitate an integrated approach to the sanitation investment planning process for urban local bodies in India. The tool is envisioned to provide stakeholders information on existing and new technologies in a manner that allows them to compare options, assess cost/benefits and make informed decisions.

CSTEP seeks to develop a proof-of-concept, scalable model of a community-owned and managed spatial data system that can aid policy and programming efforts towards meeting SDG targets (such as promoting inclusive urbanisation and equitable access to water, sanitation and health).

The project hopes to achieve the following outcomes:

CSTEP, in collaboration with the Administrative Staff College of India (ASCI) and Centre for Advocacy and Research (CFAR) aims to strengthen agencies and advance policies, regulations, and processes for increased accessibility to Water, Sanitation and Hygiene (WSH) services. The project will demonstrate an inclusive and implementable framework that looks at the cumulative impacts of different social factors (gender, age, ability, socio-economic class, etc.) and their interactions on access to adequate sanitation across the value chain.

The objective of the project was to build a Proof of Concept (PoC) of an Urban Observatory platform for Karnataka, which can carry out geo-spatial data analyses and visualisation to enable data-driven decision-making.

CSTEP is expanding its extensive work in the health sector to develop a smart-contract framework for managing child health and malnutrition. Blockchain is an emerging technology that complements AI and Big Data for providing transformative social solutions. Smart contracts and federated ledgers are the most important aspects of the blockchain technology.

CSTEP’s Health and Nutrition solution using AI is aimed at managing the health and nutrition of children and new mothers. While image-based solutions can increase the accuracy and effectiveness of health and malnutrition tracking, photo- and fingerprint-based solutions can authenticate reliable service delivery to beneficiaries. AI with advanced analytics and machine learning will provide risk assessment, causal analysis and recommendations to nodal agencies.

In December 2015, the MoEFCC notified emission standards for limiting Sulphur Oxides (SOx), Nitrogen Oxides (NOx), Particulate Matter of size <10 µm (PM10) and Mercury (Hg) emission