# Explainable Post-Occupancy Evaluation Using a Humanoid Robot
## 2 Related Work  
The literature shows a strong interest in the issues discussed in this paper. Indeed, several papers dealing with the topic inherent to our work have been recently published. Some of these are directly related to the Indoor Environment Quality (IEQ) [18; 19; 23; 32; 33; 34; 35; 36] and the relevance of the appropriate location of sensors [12; 13], while others analyzed the impact of lighting control on workers' health in-depth [20; 37; 38; 39; 40] and exploited a robot [28; 29], whereas the issues related to the post occupant evaluation were studied in [5; 6; 7; 8; 9; 10]. The approach proposed in this paper shows similarities and differences compared to the above-mentioned research. To focus on the novelty of this work, a detailed comparison is performed in the following. [PERSON] et al. [18] proposed an approach based on relatively inexpensive sensors and exploited machine learning to assess the employees' perception of indoor environment quality, introducing a new method to classify the data. The approach proposed in [32] was based on a laboratory method. It consisted of a chamber in which thermal and luminous conditions could be varied. It was found that space, luminous, and thermal parameters positively affected the satisfaction of users; however, the influence of acoustic noise was not treated. [PERSON] et al. [33] also considered the Energy Use Intensity (EUI) to estimate the performance of green structures, and the differences put in evidence by groups belonging to high and low EUI buildings were related to the energy used for the thermal environment according to the standards. In addition to the traditional approach based on a questionnaire, [PERSON] et al. [19] used a correlation and regression analysis for predicting overall satisfaction. They exploited a laboratory approach with 31 prescribed sets of conditions. Different from this, [PERSON] et al. [34] investigated the difference between aboveground and underground work spaces in terms of psychological distress, and they considered a high number of samples, classified by the OFFICAIRquestionnaire, showing that different parameters influence the two categories. [PERSON] et al. [35] faced the problem of a personalized model for thermal comfort for people sharing the same offices by using infrared thermography to predict the thermal sensation of users. [PERSON] et al. [23] conducted a large-scale survey that raised the important role of personal control for IEQ satisfaction in office buildings. This study highlighted that personal control is a crucial aspect in obtaining a healthy, comfortable, and productive environment. [PERSON] and [PERSON] [36] analyzed the problem of the thermo-physiological comfort of patients and surgeons in operating room where there was a conflict in the requirements for the thermal environment between the two categories of users. The analysis took into consideration factors related to clothing. [PERSON] et al. [12] and [PERSON] et al. [13] explained that the position of the sensors could downgrade the performance of BACSs. As a consequence, data collection had to be done by locating the sensors at suitable points. As [PERSON] et al. [12] and [PERSON] et al. [13], in this paper, we underline the crucial aspect of the measurement points. Moreover, our paper agrees with the approach proposed by [PERSON] et al. [18] based on inexpensive sensors, as well as with the works proposed in [19; 32; 33; 34], which collected data by questionnaire. Different from [18], we propose a robot endowed with a set of sensors. Compared to the others, our approach shows two main differences: (a) it aims to plan an interaction between the robot and the user for improving his/her conditions based on recommendations given by the robot; (b) it uses a dedicated software (aided by a few experimental values obtained by a sensor) to reproduce the illuminance. Besides, our paper describes a methodological approach; hence, the study of a great number of users and related analysis methods as in [18; 19; 34] can be considered as a further step.