# A Practical Approach to Deploying a Drone-Based Message Ferry in a Disaster Situation +
## 5 Conclusions  
In this paper, a drone-based message ferry is proposed to improve the urgent collection and delivery of essential post-disaster information. A message ferry is created by attaching LACS to a high performance drone. In the aftermath of a large-scale disaster, a message ferry is deployed to collect/deliver vital disaster information from and to the local headquarters (i.e., government office/disaster response coordination center) to each standalone LACS installed at the disaster shelters.  
The performance of the proposed message ferry was evaluated through an experiment. In the experiments, the inter-LACS data transfer rate (throughput) was measured. The measured data transfer rate was then used to confirm the effective transmission speed for transferring data from the local headquarters to the shelters. Our experimental results and analysis confirmed that the proposed message ferry is advantageous when transferring a large amount of data (e.g., 300 MB) at a high speed, an effective transmission speed of 2.3 Mbps when the message ferry is deployed on 802.11 ac compared to technologies such as Wi-SUN (25 kbps) and LoRa (119 kbps). As a result, disaster response efforts to collect and deliver life-saving information from/to evacuees in a timely manner can be improved.  
As part of our future work, a small and compact size LACS will be mounted on the drone which will be utilized in the actual demonstration test of the message ferry.  
Figure 12: Comparison of Effective transmission speed on IEEE 802.11 protocols. UAV’s velocity = 10 m/s. (**a**) Effective transmission speed at 1 km. (**b**) Effective transmission speed at 5 km. (**c**) Effective transmission speed at 10 km.  
In addition, the message ferry will be deployed to various disaster shelters in quasi real-time. Finally, we will consider using multiple message ferry and various routing protocols.  
Conceptualization, B.O. and T.S.; methodology, B.O.; software, B.O. and T.S.; validation, B.O., S.A. and T.S.; formal analysis, B.O. and T.S.; investigation, B.O. and S.A.; resources, S.A. and T.S.; data curation, B.O. and T.S.; writing--original draft preparation, B.O.; writing--review and editing, B.O., S.A. and T.S.; visualization, B.O.; supervision, T.S.; project administration, T.S.; funding acquisition, T.S. All authors have read and agreed to the published version of the manuscript.  
This work was supported by Council for Science, Technology and Innovation(CSTI), Cross-ministerial Strategic Innovation Promotion Program (SIP), Enhancement of National Resilience against Natural Disasters (Funding agency: National Research Institute for Earth Science and Disaster Resilience - Contract number: 22-I-9).  
Not applicable.  
This work was supported by Council for Science, Technology and Innovation (CSTI), Cross-ministerial Strategic Innovation Promotion Program (SIP), Enhancement of National Resilience against Natural Disasters (Funding agency: National Research Institute for Earth Science and Disaster Resilience - Contract number: 22-I-9). We thank Blue Innovation Co., Ltd for its support in drone-based testing.  
The authors declare no conflict of interest. The funding organization had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l} UAV & Unmanned Aerial Vehicle \\ LACS & Locally Accessible Cloud System \\ ICT & Information and Communications Technology \\ MANET & Mobile Ad-hoc NETwork \\ SIP4D & Shared Information Platform for Disaster Management \\ \end{tabular}