# A Comprehensive Study of the Use of LoRa in the Development of Smart Cities
## 4 Results of the Analysis of the Selected Works
### Analysis of the Device Layer
#### 4.3.1 Sensors  
Sensorization allows abstracting data from the physical world's to the digital world. The continuous monitoring of physical variables like temperature, humidity, and pH allow users to take decisions about specific aspects of smart city domains. Table 9 and Figure 14 present an overview of the sensors \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Subcategory** & **Indoor** & **Outdoor** & **Object Motion** \\ \hline Agriculture & & \(\bullet\) & \(\bullet\) & \\ Healthcare & & \(\bullet\) & & \(\bullet\) \\ Energy & \(\bullet\) & & \(\bullet\) & \\ Waste Management & \(\bullet\) & & \(\bullet\) & \\ Traffic and Transport & & & \(\bullet\) & \(\bullet\) \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Localization of sensors in smart applications. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Subcategory** & **Communication** & **Signal Parameters** & **Observations** & **Ref** \\ \hline \multirow{6}{*}{Agiculture} & & \(\theta 100\) m, RSSI = \(-69\) dBm, & & \\  & & PDR = 10075, SNR = \(64\) dB & & \\  & & \(\theta 400\) m, RSSI = \(-100\) dBm, & & \\  & & PDR = 80\%, SNR = \(3\) dB & & \\  & & \(\theta 700\) m, RSSI = \(-120\) dBm, & & \\  & & PDR = 41\%, SNR = \(1\) & & \\ \hline \multirow{6}{*}{Healthcare} & & \(\theta 11\) km, RSSI = \(-127\) dBm, & & \\  & & PDR = 1005, SNR = \(-127\) dBm & & LoRa transmission can generate delays in sending & \\  & & \(\theta 33\) km, RSSI = \(-121\) dBm, & & information. Therefore, it is not recommended in & [57] \\  & & PDR = 80\%, SNR = \(-16\) dB & & real-time applications. & \\  & & \(\theta 65\) km, RSSI = \(109\) dBm, & & Movement of patients can be in low-coverage areas, but & \\  & & PDR = 41\%, SNR = \(1\) \(-11\) dB & & \\ \cline{2-5}  & Tracking movement & RSSI = \(-83\) dB, & & \\ \hline \multirow{6}{*}{Traffic} & & \(\theta 05\) m, RSSI = \(-34\) dBm, & & \\  & & PDR = 100\%, SNR = \(-127\) dB & & \\ \cline{1-1}  & & \(\theta 250\) m, RSSI = \(-10\) dBm, & & \\ \cline{1-1}  & & PDR = 100\%, SNR = \(-17\) dB & & \\ \cline{1-1}  & & \(\theta 250\) m, RSSI = \(-10\) dBm, & & This situation requires a large number of sensors. & \\ \cline{1-1}  & & PDR = 100\%, SNR = \(-17\) dB & & \\ \cline{1-1} \cline{2-5}  & & \(\theta 180\) m, RSSI = \(-95\) dBm & & \\ \cline{1-1} \cline{2-5}  & & \(\theta 250\) m, RSSI = \(-10\) dBm & & \\ \cline{1-1} \cline{2-5}  & & \(\theta 250\) m, RSSI = \(-10\) dBm & & \\ \cline{1-1} \cline{2-5}  & & \(\theta 250\) m, RSSI = \(-10\) dBm & & \\ \cline{1-1} \cline{2-5}  & & \(\theta 250\) m, RSSI = \(-10\) dBm & & \\ \cline{1-1} \cline{2-5}  & & PDR = 100\%, SNR = \(-17\) dB & & \\ \cline{1-1} \cline{2-5}  & & \(\theta 250\) m, RSSI = \(-10\) dBm & & \\ \cline{1-1} \cline{2-5}  & & PDR = 100\%, SNR = \(-17\) dB & & \\ \cline{1-1} \cline{2-5}  & & \(\theta 250\) m, RSSI = \(-10\) dBm & & \\ \cline{1-1} \cline{2-5}  & & PDR = 100\%, SNR = \(-17\) dB & & \\ \cline{1-1} \cline{2-5}  & & \(\theta 250\) m, RSSI = \(-10\) dBm & & \\ \cline{1-1} \cline{2-5}  & & PDR = 10 used in smart city subcategories, based on our quality assessment. In the agriculture subcategory, some environmental parameters such as humidity, temperature, and luminosity must be measured to predict climate changes [22]. This detection can be based on a single-sensor or on a multi-sensor platform collecting microclimate data [23]. Magnetic sensors can be used in smart parking applications to detect empty park slots. This type of sensors can be influenced by nearby ferrous metal objects like bicycles or adjacent vehicles. The earth's magnetic field can also alter the data generated by this type of sensors [39]. Light sensors allow the determination of the amount of light. This is useful in plantations as well as in AAL or smart homes to turn on the lights in the night. Light sensors can be affected by outdoor lighting conditions like clouds or stationary objects that block the sun light. Dust sensors are based on the light-scattering detection technology that estimates the concentration of particles that are suspended in the air.