# A Comprehensive Review of Sensor-Based Smart Building Monitoring and Data Gathering Techniques
## 4 Occupancy Sensing  
Indoor occupancy data, combined with the capability to detect when a building or space is in use, are crucial for the operation of an intelligent building system. Knowing occupancy as well as possessing the ability to accurately predict usage patterns leads to data-driven decision making toward the minimization of operational energy consumption through the intelligent control of the HVAC systems in commercial buildings. Extensive research has been conducted on detecting occupancy in building zones using various sensors, including PIR, carbon dioxide concentration, temperature, humidity, and light beams, with the primary goal of determining whether a specific area is occupied, as described by [PERSON] and [PERSON] [44]. Motion or occupancy sensors operate by detecting infrared energy or by emitting ultrasonic or radio waves and measuring their reflection off a moving object. A promising approach for measuring occupancy described by [PERSON] et al. [45] is the implicit sensing method, which leverages existing IT infrastructure to infer occupancy counts. These sensing methods operate on the assumption that building occupants modify their environment, and these changes can be detected through various sensing mediums, as explained by [PERSON] et al. [46]. Depending on the involved infrastructure, there are three groups of implicit occupancy evaluating techniques: (i) Tier I, which requires no additional infrastructure, only data collection and processing, (ii) Tier II, which needs additional software to access data within the existing infrastructure, and (iii) Tier III, which necessitates both additional software and hardware for occupancy estimation. The occupancy resolution level varies depending on the application. For example, sometimes it is enough to determine the occupancy of a particular zone, whether complicated energy-saving systems may require both the number of occupants in different zones, and the fluctuations in occupancy intensity throughout the day [44]. As proposed by [PERSON] et al. [45], the occupancy resolution can be measured in three dimensions: spatial resolution, temporal resolution, and occupancy resolution (Figure 3). 1. Spatial (zone) resolution: building, floor, room;
2. Temporal resolution: day, hour, minute, second;
3. Occupancy resolution: * Level 1: occupancy: at least one person in a zone;
* Level 2: count: the number of people present in a zone;
* Level 3: identity: who they are;
* Level 4: activity: what actions they are performing. \begin{table}
\begin{tabular}{l c c} \hline
**Flow Meter Type** & **Cost** & **Accuracy, \%** \\ \hline Mechanical & low & 1\% of flow rate \\ Vortex & medium & 0.65\% liquid \\ Electromagnetic & medium & 0.15\% of flow rate \\ Ultrasonic & high & 1-2\% (wetted), 3–10\% (non-invasive) \\ Turbine & low & 0.25\% of flow rate \\ \hline \end{tabular}
\end{table} 
Table 2: Cost and accuracy of different liquid flow meters [41]. [PERSON] et al. [47] propose the possibility of adding Level 5 as well to track where an occupant was before. In this context, Level 5 represents the movement history of a specific occupant across various zones within the building, which is crucial for designing proactive comfort systems. The most frequently used sensors for occupancy detection include the following:  
* PIR sensors--detect changes in thermal radiation on their surface caused by the movement of occupants. They are low-cost, energy-efficient, and easy to deploy in environments. PIRs are usually wireless, powered by batteries or photovoltaic cells. The operation of PIR sensors in lighting control works as follows: the lighting system turns on the lights when movement is detected and switches them off if no movement is detected for a specified period [46]. The notable drawback of PIR sensors is their poor performance at detecting small motions. Additionally, since PIR sensors work by detecting heat emitted from humans, they may fail when the weather is hot or when placed close to the HVAC system [18; 48].