🌍 Update: Humanscapes project wins the Green Solutions Award in the UN COP26 summit 2021 at Glasgow!!

Building-performance

Python Script written to process and analyse the thermal performance of Humanscapes Habitat using sensor data from the buildings. The script also uses the datasets of ASHRAE and CBRI.

Parameters calculated

Sensors were deployed in various locations in Humanscapes habitat, and data on light intensity(lux), humidity(relative and absolute), ambient room temperature, surface wall temperature(inner and outer), roof surface temperature(inner and outer), clo values of clothing and black bulb temperature were continuously recorded.

The parameters calculated using the above data are as follows:

Thermal comfort:

Tropical summer index;

Predicted mean vote;

Predicteed percentage dissatisfied (gives an idea of comfort levels at any time in the building);

Heat stress distribution;

Compute the Fan wind velocity required for optimal comfort for all times.

Thermal performance:

damping percentage;

depreciation factor;

time lag;

thermal performance index;

instantaneous damping.

other outputs include the maximum, minimum and average of all the readings on a daily basis. Using these parameters, the thermal performace of humanscapes habitat were calculated, and also strategies both active and passive were proposed to optimise the energy usage and thermal performance.