# ECC: Passenger Counting in the Elevator Using Commodity WiFi
## 1 Introduction  
With the development of cities, the number of elevators has surged, and elevators have become an indispensable smart device for the household, which not only brings great convenience to people's lives but also provides more space for city construction. However, the emergence of elevators also introduces new safety problems. For instance, the unbalance of the elevator's counterweight is one of the vital factors affecting elevator safety [1]. Traditional elevators only care about whether the overall load is overweight, not the mass of the actual load. Therefore, they employ a rated counterweight based on their maximum load capacity instead of the elevator's actual load. The principle of elevator operation is achieved by the movement of a directional pulley. One side of the pulley is connected to the elevator, and the other side is connected to the counterweight. When the elevator is running, it produces friction between the rope and the pulley to control the movement of the elevator. If there are few or many passengers in the elevator, the overall weight of the passengers will be seriously imbalanced to the counterweight. The imbalanced weight on both sides of the rope requires the drive motor to output more power to ensure the elevator keeps running at an even speed. Continuous operation increases the wear of the rope and multiple components, which may cause accidents and increase energy overhead. Hence, regular maintenance of the elevator is very important [2, 3]. According to the statistics, more than 10% of accidents are caused by components or protection devices malfunctioning due to the elevator counterweight problem. Therefore, many studies [4] have improved the counterweight system of the elevator to reduce the safety risk. For instance, [PERSON] and [PERSON] [5] propose a passive vibration control device that can effectively reduce the risk due to the imbalanced counterweight by constraining the motions of two rails through intermediate ties to reduce the contact load. However, it requires improving the elevator hardware, which is difficult to implement in actuality. If the number of passengers in the elevator can be accurately estimated, the rule of the passenger flow at different periods can be grasped, and then the actual load range of the elevator can be inferred. In this way, the counterweight can be regularly maintained and adjusted based on the actual utilization rate of the elevator, thereby enhancing the elevator's safety and saving energy overhead. In addition, excessive passengers may cause the elevator to be overcrowded and introduce other safety issues for the passengers. Traditional sensors-based crowd counting approaches, such as the infrared sensor, camera, mobile devices, etc., either require the deployment of extra infrastructure or the cooperation of occupants to carry dedicated devices, which are intrusive and inconvenient for pervasive implementation. With the development of WiFi, signals have covered whole buildings, so the passive sensing approaches based on WiFi sensors have received more attention. These approaches can effectively overcome the drawbacks of the above methods and solve the privacy issue. Moreover, WiFi can solve the problem of weak mobile phone signals in elevators and enable people to keep in touch with the outside world in emergencies. In summary, the current sensors-based crowd counting approaches can be classified into vision-based and non-vision-based approaches. Vision-based approaches [6; 7; 8; 9; 10] mostly use image recognition for crowd counting. However, since the European Union implemented the general data protection regulation (GDPR) [11] on 25 May 2018, which aims to protect users' privacy and data security, the monitoring data captured by cameras in public venues cannot be made public arbitrarily. In this context, most product and system developments prioritize privacy and establish a sensing and detection platform for people and biological monitors that do not rely on captured video or identification data.