What We Do
Sensor Testing & Evaluation
Independent performance assessment of air quality sensors through laboratory and field-based studies to ensure reliability, accuracy, and suitability for real-world deployment.
Hyperlocal Monitoring
Deploying sensor networks to generate high-resolution air quality data, enabling localized insights and evidence-based environmental decision-making.
Capacity Building & Outreach
Conducting training programs, workshops, and awareness initiatives for government agencies, researchers, communities, and industry stakeholders.
Institute–Industry Collaboration
Bridging academia, research institutions, industry, and policymakers to foster innovation, knowledge exchange, and scalable air quality solutions.
Our work
Evaluation
Indi-SET is an indigenous facility designed in accordance with international standards for scientific and independent testing, calibration, and training for LCS technologies. CSTEP has developed the necessary architecture, framework, and capacity to evaluate multiple outdoor air sensors in a structured manner.
Indi-SET (Bengaluru) is equipped with a real-time air quality monitoring station (AQMS) comprising various reference-grade instruments for monitoring key air pollutants, including particulate matter (PM₂.₅ and PM₁₀), ozone (O₃), carbon monoxide (CO), and nitrogen dioxide (NO₂), as well as an automatic weather station. The real-time measurements of aerosol chemical and elemental composition are conducted at Indi-SET, using an Aerodyne Time-of-Flight Aerosol Chemical Speciation Monitor (ToF-ACSM), an aethalometer (Magee Scientific AE33), and an Xact 625i Ambient Continuous Multi-Metals Monitor. In addition, the real-time aerosol number-size distribution spanning 4 nm to 29.4 µm is measured using a combination of aerosol spectrometers such as a Scanning Mobility Particle Sizer (SMPS), a PALAS-FIDAS 200 S, and a GRIMM-EDM 280. The facility also has a PM sequential sampler (Met One Super SASS) for filter-based monitoring.
Indi-SET began by evaluating sensors from six manufacturers over 1 year, revealing notable results. It was observed that manufacturer-reported values were less accurate than those from the reference measurements. However, applying a localised calibration model improved LCS performance, particularly for gas sensors. This finding helped the manufacturers to improve their sensor performance by enhancing the existing sensor configurations and calibration models.
Field deployment
Achieving clean air for all requires air quality information that is timely, spatially representative, and accessible to everyone. Traditional regulatory monitoring stations provide highly accurate measurements but are limited in number due to their high installation and maintenance costs. Low-cost sensors (LCS) can complement these networks by enabling dense and scalable air quality monitoring.
1. Expand Monitoring Coverage
Low-cost sensors can be deployed across neighbourhoods, schools, industrial areas, traffic corridors, and rural regions, creating a dense monitoring network that captures local pollution variations and identifies pollution hotspots that may be missed by sparse regulatory stations.
2. Generate Hyperlocal Air Quality Information
Air pollution can vary significantly within a city. Sensor networks provide street-level and community-level information, helping residents, researchers, and authorities understand where and when pollution levels are highest.
3. Support Evidence-Based Decision Making
Continuous monitoring data can help policymakers:
- Identify major pollution hotspots.
- Evaluate the effectiveness of pollution control measures.
- Prioritize interventions in high-exposure areas.
- Track air quality improvements over time.
4. Enhance Public Awareness and Community Participation
Real-time air quality information empowers citizens:
- To make informed decisions about outdoor activities.
- Reduce personal exposure during high-pollution episodes.
- Participate in community-led environmental initiatives and advocacy.
Data
Low-cost sensor networks can bridge critical monitoring gaps, generate hyperlocal air quality insights, empower communities, and support data-driven interventions, making clean air management more inclusive, scalable, and effective.
To support this ecosystem, the Air Quality Data Management System (AQ-DMS) has been developed to facilitate centralized data collection, quality assurance, visualization, analytics, and dissemination of air quality information from distributed sensor networks.
Frequently Asked Questions
Everything you need to know about Indi-SET, low-cost sensors and our programmes.