## 4 LoRaWAN-Based Outdoor Positioning in Application-Specific IoT Domains
### Comparative Analysis and Discussion  
A summary of the different requirements of IoT systems is presented in Table 3. Location estimation accuracy and latency in smart factories and healthcare systems have high priority. Smart factories and healthcare are critical and hard real-time systems. A location error or latency higher than an acceptable threshold can lead to safety harms while lower location estimation accuracy in smart transportation and smart cities is acceptable. Energy consumption in smart healthcare and the smart city because of battery restriction is a limitation. Smart transportation and smart city have a dynamic with high mobility speed environment. Therefore, the proposed method for them should be scalable to handle their dynamic environment.  
A summary of the different proposed methods for IoT-based systems localization is provided in Table 4. A fundamental challenge of Industry 4.0 is the presence of multipath effects. Different proposed methods in this category try to improve accuracy by adopting different technologies but there is a need to determine the environment error source and their effect on the signal. Accuracy and power consumption are the most effective factors for a smart healthcare system. Most of the proposed methods in this category try to improve location estimation accuracy using GPS technology but it leads to increase power consumption. Low mobility and environmental dynamics make it possible to determine and predict the effect of environment error sources on signals to improve accuracy and power consumption simultaneously. Due to the highly dynamic environment of smart transportation, system latency reduction, and scalability. By adopting different technologies, proposed methods try to provide context-aware solutions and improve these factors. Finally, as power consumption efficiency in a smart city is an important factor, multi-technology networks and resource-aware have emerged as an important technology to improve this factor [133; 134; 135; 136].  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Reference** & **Application Domain** & **Purpose** & **IoT Localization Approach** \\ \hline [PERSON] et al. (2018) [90] & Industry 4.0 & \begin{tabular}{c} Asset localization \\ and tracking \\ \end{tabular} & GPS and LoRaWAN \\ \hline [PERSON] et al. (2021) [93] & Industry 4.0 & \begin{tabular}{c} Agriculture sensor \\ nodes localization \\ \end{tabular} & LoRaWAN and Wi-Fi \\ \hline [PERSON] et al. (2020) [95] & Industry 4.0 & \begin{tabular}{c} Performance evaluation \\ of the LoRaWAN \\ \end{tabular} & \
\begin{tabular}{c} Number of Nodes and \\ transmission interval \\ \end{tabular} \\ \hline [PERSON] et al. (2020) [96] & Industry 4.0 & Mobile robotic localization &
\begin{tabular}{c} UAV aided with \\ LoRaWAN \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table}
Table 4: Summary of different proposed method for IoT systems localization.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Application Domain** & **Accuracy** & **Latency** & **Energy Consumption** & **Scalability** & **Security and Privacy** \\ \hline Smart Factory & ✓ & ✓ & * & * & ✓ \\ Smart Healthcare & ✓ & ✓ & ✓ & * & ✓ \\ Smart Transportation & * & * & * & ✓ & ✓ \\ Smart City & * & * & ✓ & ✓ & ✓ \\ \hline \hline \end{tabular}
\end{table}
Table 3: Summary of different requirement of IoT systems (✓ = necessary requirement, * = unnecessary requirement).