# An Action Classification Method for Forklift Monitoring in Industry 4.0 Scenarios
## 2 RFID Gates  
A UHF-RFID gate is usually composed of a UHF-RFID reader connected to one or more antennas and possibly with other optional devices. Typically its main task is the identification of crossing tagged assets, being goods, people, or vehicles, such as forklifts or pallet trucks. However, an RFID gate able to provide the direction of transit of the identified object/person, can allow a complete awareness of the asset locations in plants or warehouses. Typically, two main problems occur when deploying an RFID gate in an industrial environment. First, due to the large beamwidth of standard reader antennas and the multipath effects typical of an indoor scenario with metallic objects and surfaces, the target assets crossing the gate are identified together with other static or moving tagged items nearby the gate, so stray read events may occur [13]. Second, the tag reading rate can be slowed due to the presence of the other tags demanding the communication channel resources, thus introducing a non-null probability that the tag on the target asset does not respond to any interrogation query during the crossing action [14]. The multipath effect could also affect the correct detection of the target RFID tags due to the fading effect of the communication channel [15]. To mitigate these issues, solutions relying on shielded reading zones using tunnel gates [16] were proposed. However, such solutions are required for a strong modification of the work environment and are not always suitable or easy to deploy. To avoid shielding structures, other solutions were proposed in [17; 18; 19]. In [17], a localization technique is combined with the gate functionality to solve the problem of discriminating among moving and static tags. [PERSON] et al. [18] suggested using various aggregated attributes based on the low-level reader data, e.g., Electronic Product Code (EPC), Received Signal Strength Indicator (RSSI), timestamp, and reading antenna, to perform a classification algorithm in forklift truck applications, getting an overall accuracy of 95.5%. To improve the performance, the same authors extended the method by using an advanced reader antenna setup [19]. By employing a portal configuration with two readers and eight antennas, an overall accuracy of around 99% is obtained at the expense of a relatively high infrastructure cost. To determine the crossing direction of the assets, additional devices such as light or ultrasound motion sensors [20] can be used, despite the high complexity and cost of the system. Moreover, light or ultrasound motion sensors are prone to false-positives or interruptions as unexpected entities obstruct the sensors. Other systems may employ Computer Vision (CV) and RFID systems as the concept presented in [21], but CV may give rise to privacy issues and also suffers from the outage problem if the light conditions of the environment are not adequate. To limit cost and complexity of the system, solutions based only on RFID technology have been proposed. The first systems employed more than one antenna to estimate the crossing direction of assets by processing the detection information and the RSSI measurements. In [22], a method was proposed that uses the difference in the crossing time of two antennas aligned along the gate crossing direction without additional external sensors. In [23], a similar method was proposed relying on active RFID tags and based on creating different interrogation zones for each antenna. In [24], a double antenna scheme to control the access of children at a school door was proposed. The antennas are placed on the school door, one facing the inside, the other the outside. Phase-based solutions [25] can be useful as the backscattered signal phase varies significantly with the motion of tagged assets, and can be profitably used to allow the usage of a single antenna, thus reducing the infrastructure cost. An example of an RFID phase-based access control system exploiting a single antenna was presented in [26] for tagged people crossing-direction discrimination.