Contributors and workers: Abhijit Trimukhe, Chandbhai, Almas, Siraj and Swastik Harish

One of the critical gaps in our understanding of heat and its impacts on people in informal settlements is simply the lack of data on temperature, humidity and other climatic parameters in such places. Weather data is typically restricted to government weather stations that are usually located in airports and other public institutions. Private weather stations do not share data publicly. The measurement of even simple climatic metrics in informal settlements is extremely rare. We aimed to remedy this situation to some extent by undertaking an extensive data collection exercise on climatic parameters in some of the research sites.

In February, 2023, the research team deployed about 35 data loggers in and around 15 houses and public areas (shops, schools, streets used for sitting) in Singareni Colony. The method used to select locations was a combination of their building material quality, the orientation of the wall with the most exposure to the external environment with respect to the cardinal direction, the uses to which spaces were put to and, whether the roofs of the rooms were exposed to the sun or not (whether they were the uppermost floor, in other words). Another wave of deployment was carried out in Bholakpur, Hyderabad in July, 2023, wherein about 12 data loggers were installed in 4-5 houses and other inhabited spaces (shops and schools). An Automated Weather Station (AWS) was also installed in both locations.

The following link takes the viewer to the data dashboard for all the data collected so far. The data is collected approximately monthly by community fellows who have been trained to do so, and provided with the required hardware and software for the task.

A few notes on how to use the dashboard:

• If prompted for access credentials, use user for the username and the password. This is only meant to prevent random and/or automated access and consequent processor and memory resource drainage.
• Once you reach the dashboard, select a location. Currently the options are Singareni Colony and Bholakpur.
• Thereafter, choose any set of filters within and between building material quality, orientation of the room, use of the room and exposure of the roof of the room.
• The dashboard backend is built using the open source programming language R and its CRAN packages, and hosted on shinyapps.io as an instance. It will take a few seconds to parse and average the data into 1-hour slots for the chosen filters.
• You can also choose a date period to further filter the data.
• The filtered data can be downloaded as a comma separated values (csv) file and also visualized on the app instance by going to the appropriate tab available near the top of the dashboard. As you choose or remove filters, the application reprocesses the data, so be patient for a few seconds till it does so.
• The AWS data for the corresponding period is also available as a tab, as is a visualization of the parameters: outdoor temperature, outdoor humidity, heat index, rain, wind speed and direction.

The AWS installed at Bholakpur also uploads data live to the internet. Current data can be accessed at the WeatherCloud server at this link. The data is typically updated every 10-12 minutes.

Research supporting this post was supported by funding from the Economic and Social Research Council’s (ESRC), UK Global Challenges Research Fund (GCRF) for the project, Cool Infrastructures: Life with Heat in the Off-Grid City (Award No: ES/T008091/1).