## 2 State of the Art
### Systematic Literature Review  
The collection of articles relevant to this study was systematically conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [13], which are a set of evidence-based recommendations aimed at improving the transparency and reproducibility of systematic reviews. The PRISMA framework is widely adopted across various disciplines to ensure that literature reviews are conducted rigorously and comprehensively. A detailed step-by-step procedure was followed, which is visually represented by the flowchart in Figure 1. This process is further detailed in the subsequent sections. The literature search was carried out using the Scopus and Web of Science databases, ensuring a comprehensive review of pertinent studies.  
Regarding the articles gathering, the following terms were searched: \"damag\" good\", \"damag\" in transit\", \"freight transport\" damage\", \"damag\" freight\", \"transit damage\", \"freight disrupt\", \"deliver\" disrupt\", \"cargo damage\", \"cargo loss\", \"package damage\", \"glass damage\", \"bottle damage\", \"truck transport\" damage\", \"pallet damage\", \"predict\" model\", \"prevent\", \"forecast\", \"anticipat\", and \"damag\" claim predict\".  
Firstly, a search on both databases was performed combining the previous terms into the following query: (\"damag\" good\" or \"damag\" in transit\" or \"freight transport\" damage\" or \"damag\" freight or \"transit damage\" or \"freight disrupt\" or \"deliver\" disrupt\" or \"cargo damage\" or \"cargo loss\" or \"package\" damage\" or \"glass damage\" or \"bottle damage\" or \"truck transport\" damage\" or \"pallet damage\") AND (\"predict\" model\" or \"prevent\" or \"forecast\" or \"anticipat\"); OR \"damag\" in transit\"; OR \"package\" damage\"; OR \"transport\" damage\"; OR \"damag\" claim predict\". This query was formulated following a series of preliminary experiments that tested various combinations of topic-related terms and Boolean operators, tailored to meet the objectives of this review.  
The query yielded a total of 411 results. Figure 1 illustrates the distribution of the results across the two databases and details the process used to determine the final selection of articles for the literature review. Initially, duplicate entries were removed. Subsequently, the titles and abstracts of the remaining articles were examined for relevance, and those deemed irrelevant were excluded. Articles that were inaccessible in full-text form were  
Figure 1: PRISMA diagram of the selection process of the articles reviewed in the current study.  
then eliminated. Finally, after a thorough review, the articles deemed unsuitable for the study were also excluded, resulting in a total of 14 articles to be reviewed.  
The selected articles were systematically categorized into two distinct groups to facilitate a detailed analysis of the various methodologies employed. The first category, Cargo Damage Classification Techniques, encompasses studies that focus on the methods and technologies used to classify cargo damage. This grouping allows for a concentrated examination of the techniques and tools applied in understanding and categorizing types of cargo damage. The second category, Prediction of Product Behaviour During Transport and Handling, includes research that investigates predictive models and assessment methods for monitoring product behaviour throughout the transportation and handling stages. This classification highlights studies aimed at forecasting potential issues and enhancing the resilience of products during transit, and are presented next.