# Sensors for Sustainable Smart Cities: A Review
## 3 Results
### Sensors
#### 3.3.6 Sensors for Energy Efficiency  
Energy is an essential resource for the operation of the many activities occurring in cities [14]; therefore, the efficient use of this resource is paramount to reduce costs and promote environmental and economic sustainability [129]. The main sinks of energy consumption in urban communities are those associated with industrial and transport activities, buildings operations, and public lighting. In this section, we focus on the sensors used to monitor the usage of energy ground transport in buildings and public lighting. Since sensors for industrial activities were covered in previous sections. _Ground transportation_ represents the main sink of energy consumption (\(\sim\)45%) and the major source of air pollutants in urban centers [130]. Car manufacturers report the specific fuel consumption (SFC measured as L/km) of their vehicles using laboratory test protocols. However, they do not report these data for heavy-duty vehicles. Furthermore, the real vehicles' energy consumption is affected by human (driving), external (traffic, road, and weather conditions), and technological factors. For gasoline and diesel-fueled vehicles, the common strategies to measure real-world fuel consumption on a representative sample of vehicles are: (i) measuring the fuel's weight before and after a specific distance being driven (gravimetric method), and (ii) measuring instantaneous fuel consumption through the on-board diagnostic system (OBD method). This second alternative uses optical sensors to measure the engine RPM, pressure sensors to measure the inlet air flow. The engine computer unit (ECU) uses these measured data to determine the engine fuel injection time. In addition, a global position system (GPS) determines the vehicle's speed. Using all this information, the ECU reports via OBD the vehicle's instant fuel consumption. Currently, there are commercially available readers that read the OBD data and send the collected information to the cloud. Using these technologies, telematics companies monitor thousands of vehicles in operation [131; 132; 133]. Similar systems are available for electric vehicles. We recommend this OBD-based alternative to measure the real energy consumption in ground vehicles. _Buildings_ represent 40% of total energy consumption [134] and 30% of greenhouse gas (GHG) emissions [129; 134]. The main physical and non-physical factors involved in indoor environment quality are shown in Figure 9[134]. These factors are measured using wireless sensors [135; 136], virtual sensors [137], and artificial neural networks [16]. Energy consumption in buildings is associated mainly with (i) thermal comfort (operation of heating, ventilation, and air conditioning-HVAC systems); (ii) indoor lighting; (iii) various electrical loads (operation of electric equipment); (iv) thermal loads (use of fuels for heating and cooking), and (v) indoor air quality (pollutant concentration, odor, and noise) [138; 139]. Table 2 shows the variables used to grade these five aspects and the sensors frequently used to measure these variables. However, additional variables influence energy consumption, such as the occupation level [140], and the building's structural design [141], and outdoor conditions (temperature, humidity, pressure, and solar radiation). Therefore, additional sensors are used to measure them. Some research works have focused on designing intelligent building management systems (BMS) that use, in real-time, data from the sensors listed above and take actions oriented toward the reduction in energy consumption, such as turn lights off, closing doors and windows, etc. [142]. _Public lighting systems_ represent almost 20% of world electricity consumption, and it is responsible for 6% of GHG [143]. Therefore, it is essential to centralize street lighting control and smart management to reduce energy consumption, maintain maximum visual comfort and occupant requirements [139]. The variable most used in lighting systems is the lighting power density (LPD) [138].