# 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 Application Layer  
The inclusion of ICT and sensors in different subcategories of the smart city such as agriculture, healthcare, environment, traffic, safety, and industry allows the creation of a strategic vision of the city. The use of LPWAN technologies is considered in smart city because it allows reaching large areas of coverage, while consuming a low amount of energy. Figure 10 shows a basic overview of our analysis of LoRa usage to support different kinds of applications, related to agriculture, healthcare, energy, industry, safety, environment, and traffic. The coverage of LoRa implementations identifies both urban and rural areas. Figure 10: Types of LoRa applications in the smart city. Figure 9: Methodology used for a systematic literature review and a qualitative analysis of LoRa-related papers. The use of IoT in different domains of the smart city establishes an ecosystem which includes: (1) technical aspects such as frequency of operation, energy levels, and sensitivity thresholds; (2) use of technical components such as sensors, imaging devices, and data capture; (3) use of data analytics processes based on cloud or fog infrastructures; and (4) parameters to be sensed and monitored according to the objective and particularity of each smart city domain. For instance, in the case of smart agriculture, parameters such as temperature range, humidity values, and soil shade are relevant to determine the feasibility of planting and harvesting. This data analytics process can be very useful for pest control in agriculture. According to our SLR, some components of the IoT ecosystem are used in the different subcategories of the smart city, for instance, fog or cloud computing are used for the storage and processing of the data collected by sensors in agriculture, transportation, or healthcare. Other components are more commonly used in some applications of specific subcategories of the smart city; for instance, biomarkers or wearables are most commonly used in healthcare applications. Complementary technologies like Radio Frequency Identification (RFID), Global Position System (GPS) and Drones are used to provide additional information related with geographical conditions. Figure 11 shows the most used components to create IoT ecosystems in smart city applications according to the qualitative analysis performed in this work. According to our qualitative analysis, Lora-based IoT ecosystems for smart cities comprise five relevant components, i.e., sensors, complementary technologies, data science, citizen interaction, LoRaWAN. The LoRaWAN allows the delivery of the data generated by different sensors and IT supplements to the data science component. Such data, through the data analysis process, are converted to patterns or anomalies, which are used by citizens and city administrators for adequate decision-making. On the other hand, sensors allow obtaining parameter values that are relevant in each subcategory of the smart city. In this sense, we identified three groups of sensors that are the mostly used in IoT solution based on LoRa. The first group of sensors is focused on obtaining parameter values such as pH, loan, and temperature, which are related to operating conditions of certain city domains (e.g., agriculture, energy, and environment). For instance, in agriculture, the pH and temperature values allow the identification of conditions that are suitable for planting or harvesting. In water management, the pH value allows the evaluation of water quality. The second group of sensors includes those devices focused on the measurement of gases (e.g., air pollution, oxygen, and ozone). This type of sensors (according to our qualitative analysis) are greatly accepted especially in the environmental domain to evaluate the levels of pollution in a city. Finally, the third group includes those sensors used for motion detection.