# A Smart Parking Solution Architecture Based on LoRaWAN and Kubernetes
## 3 Analysis of Previous Works
### Analysis of Works That Focus on Backend Solutions  
The reviewed papers propose several ways to deploy a smart parking solution. Some of them emphasize on the types of sensors that might be used for deploying such solution as in [24]. Meanwhile, there are others that do not use specific purpose sensors and they attach sensing modules to Arduino or similar devices. These microcontrollers do not have the same energy autonomy properties as specific purpose sensors. Moreover, these microcontrollers are not IP68 compliant which make them no suitable for adverse weather conditions. Sensors must be able to sense the presence of a vehicle no matter the weather. Therefore, sensors in a smart parking solution have to be able to work under severe weather conditions (i.e., rains, dust). Likewise, sensors should be able to transmit information over long-range perimeters with low energy consumption. These sensors should not be invasive as RFID, but effective when determining vehicle presence and avoid false-positive detections. Based on that, magnetic sensors are the ones that best fit the detection requirement and will be part of the proposed solution.  
Wi-Fi, BLE and Zigbee are appropriate for short distances (less than 500 m). Network connectivity must reach long distances. In real conditions, parking slots are bigger and cover hundreds of square meters particularly in places like hospitals, universities, schools, cities. LPWAN protocols are suitable for covering long-range distances at low power consumption. Protocols like SigFox, LoRaWAN or NB-IoT could be considered for implementing a smart parking solution. Due to its versatility and openness, LoRaWAN is suitable protocol for a smart parking solution as discussed in [14; 16; 20].  
In terms of messaging, some solutions agree that MQTT is a suitable protocol for moving information collected from sensors to a backend infrastructure as in [17]. However, such architecture proposes the use of a unique server with no redundancy for collecting information and then storing information in a database. In that scenario, data would be lost as sensors do not have a mechanism for queuing packets. Therefore, not considering a redundancy mechanism would compromise the availability of information for further processing to obtain a particular result.  
Smart parking solutions are intended to serve thousands of users (citizens). The backend infrastructure is in charge of processing and sharing data with their different actors. These actors could be other systems, services or citizens. The number of actors is constantly growing and tend to be unlimited. An appropriate way to keep up with this growth is by using components that could grow at the same rate and that provide appropriate levels of availability. Although using one physical server per service involved is a best practice, it does not allow a high level of scalability and availability. This a technical and economic limitation that would considerably increase the cost of the final solution. An approach to address these issues is by clustering nodes involved and avoid using physical servers. Kubernetes are a feasible alternative to configure a cluster of every service involved (i.e., data storage, messaging, publishing) as every node has its own computational resources [23].