## 2 State of the Art
Apart from the above-mentioned obstacles, another problem is the intricacy of ensuring that the system is interoperable with other existing systems inside the company [5]. Automatic identification technologies are necessary for a quality traceability system. These technologies are especially significant for traceability in the industrial setting, and they have grown in a way that has allowed for the automation of traceability processes over time, which has decreased the expenses related to data acquisition [7]. There are several support technologies available at the moment, and the technology to be used must match the amount of data needed for its intended use. However, it should be noted that data management and transmission, along with the development of the most relevant solutions for each situation, are essential components of traceability systems [9]. The acronym AIDC covers all technologies that allow the identification of objects and people through automatic data capture, i.e., the direct input of data into a micro-processor-controlled device, and many of these tools do not require human involvement. As already mentioned, the alternative to automatic data collection is manual data collection. This usually requires a worker to record the information on paper and then enter it into a computer using a keyboard. This situation has several drawbacks, not only regarding the data collection operation but also regarding data entry, the most notable of which are the following problems [5]:  
* There is an average error rate when typing on a keyboard that reaches one error for every three hundred characters to be entered;
* Manual methods are intrinsically more time-consuming than automated methods, but when manual practices are used, there is a time lag between carrying out the activities and entering them into the respective software, i.e., the information is not available in real-time;
* Labour costs are associated with the time spent by workers on this type of action. However, when the operation is aided by such automatic recognition technologies, these disadvantages almost completely disappear. Generally speaking, all automatic identification systems consist of three primary parts [7]:  
* Data encoder--the component responsible for creating codes (a code corresponds to a set of symbols or signs that usually represent alphanumeric characters), so that when coding is carried out, the characters are translated into a code, readable by the respective complementary machines of the tracking system, which takes the form of a label attached to the objects to be identified;
* Reader--a device used to read the encoded data;
* Data decoder--a component that transforms the data read by the reader into digital data, so that the information contained in the code returns to its initial phase, i.e., it is presented in alphanumeric characters. Barcodes and RFID are the most widely utilised AIDC technologies in industrial manufacturing. Their most frequent operational uses include receiving and shipping commodities, storing completed goods, keeping an eye on the production process, and performing assembly and quality control operations, among other things. Operators are needed in the application of a number of these technologies to collect data, usually by operating the identification equipment. For this reason, rather than being entirely automatic--that is, when no worker or employee needs to be involved in the process--these techniques that require human intervention are referred to as semi-automatic or partially automatic [3]. On the one hand, barcode technology essentially consists of reading by optical readers, by emitting laser rays into the respective codes, with these rays being absorbed by the black bars or reflected by the white spaces (when they fall on the given barcode), where the sequence of bars, some narrower and others wider, represents the information contained in that code.