---
# System prepended metadata

title: 'Literature review - California, USA'
tags: [BRAIN_Lab]

---

# Literature review - California, USA
###### tags: `BRAIN_Lab`

## [Targeted occupant surveys: A novel method to effectively relate occupant feedback with environmental conditions](https://www.sciencedirect.com/science/article/abs/pii/S0360132320305035)

### Highlight
We developed the targeted occupant survey (TOS) platform to give researchers greater flexibility in distributing right-now occupant satisfaction surveys.
design goals for our field study
1) minimize redundancy in the collected data
2) minimize disruptions to participants

### 2.2. Pilot study (Building)
We tested the TOS platform in a pilot study conducted in the David Brower Center (DBC) building in Berkeley, CA from October 20 through December 10, 2019.

### 2.1.2.Software program environment (Source code)
The **TOS platform is written in Python** (Python 2018, version 3.6.8) (Kuhlman 2012). We used **pandas and NumPy** to manage and analyze time-series data (pandas 2019; NumPy 2019). Data analysis for the pilot study was done in R Statistical Software (The R Foundation 2019, version 3.6.1) with the tidyverse package (Wickham et al. 2019). Links to the source code for the TOS platform, helper programs, and analysis can be found in the supplementary material.

### 2.1.3.Survey service (Tool used to conduct survey software)
The TOS platform can interface with any survey service that supports the download and use of data within the Python environment. We used Qualtrics Survey Software for the pilot study (Qualtrics 2014). Qualtrics uses a REST API to request survey information (Fielding et al. 2017) for subsequent download and analysis of responses. The questionnaire used in the pilot study is described in 2.2.2, and the full questionnaire can be found in Appendix A.

### 4.1. TOS platform
**Field studies of thermal comfort** are necessary to verify results of human-subject laboratory tests or to gain new insights on occupant perception and behavior in real world settings. Because office workers are often time-poor, it can be challenging to recruit them for such studies. Furthermore, researchers usually do not have control over the occupants’ indoor environment. These challenges often lead to field research methods that may not optimally collect subjective responses. The survey platform we developed is designed to address these methodological issues by performing targeted right-now surveys (TOS).

