# A Smart Parking Solution Architecture Based on LoRaWAN and Kubernetes
## 1 Introduction  
One of the most common activities of a driver in a city, is to find a parking space. Finding a parking space turns difficult when a driver is not familiar with the city or when the city has vehicular congestion. The activity of finding space is manual and demands time. An average of 30% of the vehicles on the street are looking for a parking spot and the time it takes is around 8 min in average [1]. In addition, a vehicle spends 10% of its time moving whilst the rest of the time it is stopped as mentioned in [2]. Smart parking solutions are useful because they help drivers to reduce fuel consumption, save time and money, reduce stress and increase safety as do not get distracted while finding a parking place [3]. There are several novel smart parking solutions with different architectures and ways of implementation as reviewed in [1]. However, these solutions have several limitations from the technological perspective that do not allow to have a comprehensive smart parking system. First, in terms of sensors, they are not specialized ones with specific-purpose (i.e., general sensors for Arduino, Raspberry or Espressif (ESP) boards). Additionally, communication protocols to collect data from sensors are not appropriate for handling small payloads within long distances. Some existing solutions do not emphasize on power-consumption which is required for most of Internet of Things (IoT) scenarios. Furthermore, previous solutions' backend infrastructures are based on a virtual machine approaches or traditional dedicated server deployments. In addition, these solutions do not consider mechanisms for holding data for extended periods of time in case of failure. Moreover, even though high-availability is crucial in smart parking since it provide information in real-time,most of systems do not consider this requirement. Finally, integrating previous solutions to other systems is complex and demands more effort as they do not have standardized interfaces such as APIs. One of the solutions that helps to solve the aforementioned problem is smart parking. Smart parking is one of the most remarkable use cases within smart cities context [4]. Smart parking solutions can reduce congestion, optimize parking time and reinforce traffic laws. Smart parking solutions leverage on the use of Internet of Things (IoT) technologies to expand and fulfill their purpose. IoT relies on technologies that support low energy consumption, profitability, low data rate and long-reach among others to deliver solutions that benefit humankind [5]. In this scenario, Low-Power Wide-Area Network (LPWAN) transmission technologies provide many benefits for smart parking solutions, such as wide coverage in rural and urban areas at low energy consumption. Among the LPWAN protocols, the most popular are: Narrowband IoT (NB-IoT), SigFox and LoRaWAN as stated in [5]. These protocols have similarities in terms of architecture but differ in other parameters such as frequency of operation, security and connection fees. Within LPWAN protocols, the most flexible and used protocol is LoRaWAN [6]. LoRaWAN is an open standard protocol which is the most attractive reason for being widely used. It is based on LoRa which works over Industrial Scientific and Medical (ISM) bands and does not require a connection fee like NB-IoT. Likewise, it does not require a third-party infrastructure (backend servers) for its deployment as occurs in SigFox [7]. In terms of architecture, there are several ways to deploy a smart parking solution. For instance, authors in [8] used Arduino boards as sensing infrastructure components. There are other solutions as [9] that focus on building their own sensors rather than deploying a specific purpose sensor as in [10]. This proposed solution suggests the use of specific type sensors to collect information at the sensing infrastructure layer. In terms of communications several works uses Wi-Fi for connecting sensors with backend infrastructure [11]. However, Wi-Fi connectivity consumes more power and does not cover long-range areas.