## 3 Materials and Methods  
### AIoT Hardware Infrastructure for Implementing the Residential PET Recycling Prototype  
The authors have analyzed several ARM platforms, including Arduino Uno, M5 Stack with ESP32, Raspberry Pi, and Asus Tinker Board. A comparative analysis conducted by the authors of this article, detailing the hardware and software advantages and limitations of these platforms, has been presented by [PERSON] [63]. Thus, [PERSON] et al. [63] have demonstrated the clear superiority of the Raspberry Pi and Tinker Board platforms in regard to IoT applications. Among these two platforms, [PERSON] et al. [63] highlighted the advantages of using the Asus Tinker Board, particularly in regard to scripting scenarios that do not require graphical user interfaces, thanks to its Linux-based operating system. For the current project, the Asus Tinker Board uses the TinkerOS, to support the execution of Bash scripts. This compatibility with Azure cloud services improves the system's capabilities and facilitates its seamless integration with IoT frameworks. Using the Asus Tinker Board, with its Linux-based operating system, ensures that the proposed PET recycling system can process data and respond to real-time events, which are necessary for recycling operations. The hardware system is centered around the Asus Tinker Board, which is well-suited for use in the AIoT infrastructure for PET recycling due to several key features. Its quad-core ARM-based processor ensures the handling of data processing tasks, including image recognition and real-time monitoring. The board supports high-resolution video input, and its GPIO interface enables integration with various sensors and peripherals, making it ideal for IoT applications. Figure 2 presents an overview of the AIoT components in the proposed PET recycling prototype. The IoT-based system, using the Asus Tinker Board to automatically sort PET bottles from non-PET objects, referred to as the PRS, employs Microsoft's Azure Custom Vision service for object recognition and integrates weight detection for PET bottles. The PRS components, presented in Figure 2, are as follows:  
1. Presence detection via a passive infrared (PIR) sensor, utilized to detect the presence of a person approaching the PRS. When movement is detected within a predefined range of 3 m, the system is activated and prepared for interaction;
2. Two light-emitting diodes (LEDs) that signal the status of object submission: * A green light indicates that the system is ready to receive the object, and the user can place the item into the bin; * A red light is triggered if the system is not ready to accept the object, alerting the user that they must wait before depositing the item;
3. A dedicated camera is implemented to scan a QR code presented by the user. This allows the system to identify the user and associate the recycling actions with their profile, potentially for reward or tracking purposes;
4. A second camera captures an image of the object in the input bin. This image is then sent to the Azure Custom Vision service, which performs object recognition to determine whether the item is a PET bottle or a non-PET object. The object classification results are sent back to the PRS to make sorting decisions;
5. A load cell sensor (scale) is installed to measure the object's weight once placed in the bin. The weighing scale is represented by a 20 kg load cell, with a HX71 amplifier. The scale measures the weight of the recycled materials to ensure compliance with recycling standards. This ensures that the PET bottles are properly sorted only after they have been emptied of liquid, as full or partially filled bottles will exceed the predetermined weight threshold of \(\pm\)2 g;
6. The sorting mechanism is driven by a stepper motor (Plusivo 17 HS4401) with a driver (A4988), which controls a flap that redirects the object into one of two compartments: * The PET compartment.