# Motion Trajectory Prediction in Warehouse Management Systems: A Systematic Literature Review
## 5 Findings
### Miscellaneous
[96], which is also a literature review, but mainly deals with the application of IOT in smart logistics, also includes a section on smart warehouses. They mainly mention environment sensing in the context of security, warehouse layout optimization, and warehouse management in general. As difficulties of the field, they mention (1) data security, (2) data privacy, and (3) managing the range of different solutions and their integration with each other. In an innovative manner, their paper does not merely compile existing knowledge but critically examines the deployment of IoT across various logistics functionalities, from transportation to warehousing and distribution. The paper's explicit focus on environment sensing, especially in the context of security, warehouse layout optimization, and comprehensive warehouse management, gives it a nuanced depth. Moreover, by delving into predominant challenges in the sector, such as data security, privacy, and the integration of diverse solutions, they offer practical insights in their review. However, the paper's overarching nature is a limitation. As a literature review, it may lack empirical evidence, hands-on experiments, or practical case studies to complement the theoretical discussion. For future work, several research challenges within the IoT-based smart logistics arena await tackling. Given the rapidly expanding field, empirical studies addressing these challenges, such as data security and integration issues, represent a promising avenue. In their article, [PERSON] et al. [97] highlight the significance of integrating order picking planning problems. The authors provide an in-depth examination and review of the current state-of-the-art classification in this domain, emphasizing the importance of considering multiple planning problems to design efficient order-picking systems. In particular, the review demonstrates the following: (1) Problem interaction analysis that evaluates combinations of problems with different planning horizons. (2) Effective solution of integrated operational problems using metaheuristics. (3) Underexplored relevant research opportunities in order picking optimization. The innovativeness of the research lies in their comprehensive review and classification, which underscores the interplay between various planning problems, and the subsequent guidelines offer practical solutions for warehouse managers. Yet, the study recognizes its limitations, notably the small sample size for many problem combinations and the dearth of in-depth investigations on many of these combinations. Future research opportunities emerge in developing integrated models for specific planning combinations, refining heuristic algorithms tailored for real-world scenarios and amplifying the scope of literature-reviewed or empirically studied underexplored problem combinations. The paper by [PERSON] et al. [98] sheds light on the gap between academic research and practical implementation in the context of order-picking planning. The authors argue that while academic research yields valuable insights, there is often a lack of effective translation into practical warehouse management policies. The paper provides a comprehensive classification and review of the current state-of-the-art, aiming to bridge the divide between theoretical advancements and practical considerations in order-picking planning. According to the authors, simplistic approaches favoured by warehouse managers can lead to suboptimal results. They suggest that future research should prioritize practical factors and practitioner insights into order-picking operations. Specifically, research should focus on identifying bottleneck drivers, examining warehouse safety, analyzing the impact of similar products on picking times, and developing decision-making tools for balancing workload. In addition, research efforts should evolve toward integrated solution algorithms that take into account various practical factors and interdependencies among planning problems.