Enhancing Outbound Logistics Performance through Drone-Assisted Environmental Sensing and Intelligent Less-Container-Load (LCL) Optimization

DOI

10.2991/978-94-6239-745-3_12How to use a DOI?

Keywords

Outbound logistics; Less-container-load (LCL); Drone-enabled logistics; Intelligent logistics systems; Container space optimization; Digital supply chains

Abstract

Less-Container-Load (LCL) outbound logistics operations are frequently limited by ineffective container space use, restricted environmental visibility, and manual decision-making. These difficulties result in longer loading times, more handling errors and less-than-ideal logistical performance. To facilitate real-time decision-making in LCL operations, this study suggests a drone-enabled intelligent outbound logistics system that combines automated package profiling, simulation-based container loading and environmental sensing. Before allocating containers, the suggested solution uses unmanned aerial vehicles (UAV) to record the temperature and humidity levels surrounding loading environments. These measurements are then compared to specified logistics parameters. To create effective LCL loading configurations, package parameters including size, weight and quantity are digitally profiled and processed through a simulation-based optimization module. To synchronize digital logistics documentation with physical package handling, barcode-enabled synchronization is integrated. In comparison to traditional outbound loading methods, a scenario-based logistics simulation shows increased cargo traceability, decreased manual dependency and better container space utilization. By developing an integrated digital logistics framework that combines intelligent simulation and drone-based sensing to improve operational efficiency and decision support in outbound logistics systems, this research project contributes to the depth of knowledge on logistics management.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits any noncommercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if you modified the licensed material. You do not have permission under this license to share adapted material derived from this chapter or parts of it.

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TY  - CONF
AU  - Ts. Zety Shakila Binti Mohd Yusof
AU  - Hasnieza Bt Mokhtar
AU  - Suhaina Binti Mohamed Zaki
PY  - 2026
DA  - 2026/08/24
TI  - Enhancing Outbound Logistics Performance through Drone-Assisted Environmental Sensing and Intelligent Less-Container-Load (LCL) Optimization
BT  - Proceedings of the International Conference on Research, Innovation, Sustainability, and Educations (IRISECON 2026)
PB  - Atlantis Press
SP  - 155
EP  - 171
SN  - 3091-4442
UR  - https://doi.org/10.2991/978-94-6239-745-3_12
DO  - 10.2991/978-94-6239-745-3_12
ID  - Yusof2026
ER  -