# Comparing Monitoring Networks to Assess Urban Heat Islands in Smart Cities
## 3 Choice of System Components and Programming
### Considerations of the WMO
#### 3.1.1 Automatic Weather Stations  
The WMO defines an AWS as a meteorological station at which observations are made and transmitted automatically, and it must fulfill certain requirements to guarantee the quality, accuracy, and representativeness of the measurements, minimizing any possible distortions. It prioritizes the use of the AWSs that provide RTD over those that are offline and store data. Depending on the number of climate variables monitored, AWSs are considered to be either light (generally air temperature, relative humidity, precipitation and, sometimes, atmospheric pressure), basic (adding wind speed and direction), extended (with the additional measurement of solar radiation, sunshine duration, soil temperature, evaporation and so forth), or AWOS (which include automatic observation of visibility, cloud-base height and present weather). Similarly, the WMO highlights the current tendency towards low-cost AWSs, which are usually offered as compact solutions developed through electronic embedded sensors and adapted software. Three main classes are considered: compact AWS, similar to professional meteorological stations that feature individual, calibratable instruments for each variable, housed in a cabinet with data-logging and transmission capabilities; all in one, a single unit that integrates multiple sensors, with the option to add more instruments; and stand-alone instruments, IoT devices that use low-power networks such as Wi-Fi or Bluetooth to transmit data to centralized servers and phone add-ons. Furthermore, the firmware can be developed by the manufacturer and stored in the memory of the CPU, thus limiting user access to certain functions, or it can be open programming, which allows the user to design and develop the software, generating more flexible platforms. Each component is described below. 1. Sensors  
To measure the basic climatic conditions, it is necessary to integrate air temperature and humidity sensors that are robust, need low maintenance, and do not suffer distortions when recording data. They may consist of various sensors connected to data gathering units via interfaces, or independent sensors connected to a CPU. As for uncertainty and performance, for the air temperature, the WMO recommends a measuring range of \(-80\)\({}^{\circ}\)C to \(60\)\({}^{\circ}\)C, with a resolution of \(\pm 0.1\)\({}^{\circ}\)C and a measurement uncertainty of \(\pm 0.1\)\({}^{\circ}\)C between \(-40\)\({}^{\circ}\)C and \(40\)\({}^{\circ}\)C, and of \(\pm 0.3\)\({}^{\circ}\)C for other ranges. The measurement range of relative humidity should be from 0% to 100% with a measurement uncertainty of \(\pm 1\%\). 2. Central Processing Unit  
This centralizes the data input/output operations, as well as their conversion, processing, and temporal storage, depending on the type of station and use required. The data can also be distributed among several specialized digitally connected units. As for their location, if they are situated close to the sensors, then the in situ processing is optimized and the amount of data to be transmitted is minimized; however, protection against atmospheric and electrical failures is needed. On the other hand, placing them inside increases the cabling needs and requires signal conditioning, but it does offer a greater energy stability, as well as a controlled environment. The CPU centralizes the programming tasks of the AWS, whose main functions are initialization, sampling, raw data conversion, message coding, quality control, local data storage, data transmission, and remote diagnostics and maintenance. There are other, less frequent operations in AWS, such as the averaged measurements, the manual entry of observations, data reduction, or data visualization. 3.