## 2 Overall Design
### Control System Design  
Traditional lawn lamps are generally controlled by timing, which consumes more energy [12]. The existing lawn lamps only satisfy the lighting function, which does not reflect the concept of a smart city. With the increase in outdoor lighting types, natural illumination is no longer the only factor affecting lawn dimming but also needs to consider the ambient light level brought by the surrounding lamps. Therefore, in this study, in order to optimize the above problems, an intelligent lawn lamp with adaptive dimming that combines ambient light level and pedestrian flow is studied. The lawn lamp can collect the required data through a light sensor and pedestrian flow sensor, and after the control system analyzes and processes the best dimming coefficient of the lamps and lanterns to realize multi-light control through centralized control. The control system can be divided into three layers: the data acquisition layer, the data transmission layer, the data processing and the display layer. The architecture of the control system is shown in Figure 2.  
1. Data acquisition layer: this layer collects data such as ambient light level, pedestrian flow, weather factors and electronic ballasts for controlling LED luminaires.
2. Data transmission layer: This layer consists of an ARM embedded system and a Zigbee wireless transmission module. The ARM embedded system collects the data collected by the sensors for transmission to the fuzzy controller.
3. Data processing and display layer: This layer includes the fuzzy controller that uses the given fuzzy logic to calculate the output dimming coefficients.  
In this paper, we also study the effect of CCT (color temperature) on human emotions, as good lighting design aims to create a light environment that is beneficial to human emotions and can sometimes even improve work efficiency and increase happiness [13].  
Figure 2: The architecture of the control system.  
The light source is low color warm light, which makes the interior space look warm, relaxed and stable, while high CCT and cool light will create a fresh and energetic atmosphere in the space. The park has a high flow of people from 5:00 p.m. to 10:00 p.m., which is a relaxing space for the busy workers, so the CCT is 3500 K to create a warm light environment. When the time is 4:00 a.m., it is suitable to adjust the CCT higher, so that people produce a fresh, clean feeling. On the other hand, coastal areas have more rain and fog, which will directly affect the lighting effect of the lawn lamp due to the low CCT of the light and its strong penetrating power, so in the rain and fog, control light source output with a low CCT, the process of CCT adjustment as shown in Algorithm 1.  
```
0:
0: Change of CCT;
1: Initialize hardware devices;
2: Acquisition of data;
3:for Number of time judgments do
4: Time judgment;
5: if (17:00 < =Time < =22:00) | |(Time >= 04:00)
6:for Number of weather factors judgments do
7: Weather judgment;
8: if(rain) | |(fog)
9: end
10: end
```  
**Algorithm 1** The Process of CCT Adjustment  
The lighting control method in this study is in the form of one-to-many, i.e., the centralized controller is externally connected to facilities, such as environmental information collection sensors and pedestrian flow collection sensors, and the sensors will upload the real-time collected data to the centralized controller to achieve the dimming coefficients of the lamps through the fuzzy controller. The physical location of the centralized controller is generally arranged in front of its management area, and the thesis will investigate the lighting control strategy for this one-to-many form, which can be used for the corresponding brightness adjustment control operation of multiple lamps.