Abstract
This study examines the operational impacts of a proposed law that would prohibit federal agencies from purchasing Unmanned Aircraft Systems (UAS) from certain countries, such as China. This legal restriction would have reaching consequences considering the increasing use of UAS in aspects of U.S. security, including law enforcement surveillance, rescue operations and traffic monitoring. To assess the effects on state and local public safety agencies we conducted a review of previous research and statistical data related to similar situations. The available data indicates that a significant number of drones used by these institutions are manufactured in China. These findings underscore the importance and vital services provided by Chinese made UAS compared to studies. The objective of this paper is to educate stakeholders about the ranging implications of this ban focusing on the need for planning and exploring possibilities, for domestic UAS manufacturing or alternative sourcing.
Introduction
Unmanned Aircraft Systems have revolutionized the operational dynamics of local and state public safety agencies in the United States. Their swift integration into these agencies underscores their vast potential in enhancing safety, efficiency, and real-time responsiveness. Whether it's assisting in search and rescue missions, providing aerial perspectives during wildfires, or offering real-time surveillance for crowd management, UAS have proven to be invaluable. The rapid growth and adoption of this technology are testament to its transformative capabilities, setting a new standard for public safety operations across the nation. With the passage of the 2020 National Defense Authorization Act, federal agencies have effectively been banned from acquiring funding to buy UAS from Chinese manufacturers. This decision has raised concerns among individuals who believe it will have an impact on the operational and financial needs of local and state public safety agencies who currently operate fleets of UAS that are mostly comprised of Chinese UAS. The aim of this study is to evaluate the operational and financial consequences of a proposed similar ban on state and local public safety agencies from operating Chinese-made UAS. To achieve this goal, we have analyzed data and relevant literature pertaining to scenarios and their outcomes.
As part of the inquiry, we conducted an analysis on data from incidents in the past and their consequences. This research helped us gain an understanding of the operational challenges that state and local participants would face due to the ban. It's important to investigate and identify countermeasures for any impacts that may arise from this restriction. Additionally, being aware of the likelihood of this restriction can influence our decision, on whether to proceed with enforcing the ban or completely abandoning it taking into consideration the consequences of action.
In the US, state and local security and safety agencies frequently deploy Chinese UAS. Law enforcement, search and rescue, and emergency response have all made use of them. It is necessary to take into account the influence on these functions before prohibiting Chinese UAS systems. This study provides an extensive understanding of the implications for operations and finances. The results will help determine the role Chinese UAS systems play in the economy and if prohibiting them is the right course of action. It also assists in determining whether there are prospective alternatives for the forbidden UAS systems, i.e., whether the United States can continue manufacturing or discover other solutions to fill the needs served by the banned products.
Literature Review
Studies indicate that UAS systems are the future of defense and security. According to Gupta et al. (2013), UAVs are better adapted than manned aircraft for dangerous, risky, or mundane missions. (Gupta et al., 2013) demonstrated that UAS are extensively utilized for border security, counterinsurgency, target identification, electronic attack, and law enforcement. Their research aimed to examine UAS as an emerging technology with the potential to revolutionize warfare. Gupta et al. (2013) concluded that these systems are the future and that further research is required to determine how their use can be exploited for the benefit of future warfare. This study is pertinent to the current analysis because it demonstrates how UAS systems have benefited American security systems. Examining these advantages provides insight into the extent to which the withdrawal of Chinese UAS systems from the American market will impact American security agencies. This is particularly true if there are no potential replacements, as this would necessitate a reliance on substandard systems. This analysis examines the potential repercussions of this ban and reveals some operational facets of the use of UAS by security agencies. By identifying the operations of the UAS systems, it is possible to determine some of the ways through which there will be ramifications for the decision to ban the Chinese UAS from use by local and state agencies.
Mohsan et al. (2023) conducted a similar study to determine the UAS applications. Similar to the findings of Gupta et al. (2013), this study discovered that government agencies use UAS systems extensively for security surveillance. Mohsan et al. (2023) add that these systems are more accessible, secure, lightweight, robust, and cost-effective than manned systems. This explains why their use in security surveillance is so widespread. Mohsan et al. (2023) observe that these systems have limitations with regard to flight duration and payload, battery endurance, path planning, and flight autonomy. These exhibit functionality issues that create reservations in the use of these systems. This study is pertinent to the current analysis because it reveals UAS limitations that make them less than ideal for use by American security agencies. This could pave the way for American authorities to conduct additional research and development in order to produce superior drones. This study is useful and pertinent because it demonstrates the potential for improving existing systems and developing superior systems for use by American government agencies. In this way, the prohibited systems would have less impact on local and state authorities if alternatives could be developed.
Watts et al. (2012) have demonstrated that civilians also utilize UAS systems. These systems are utilized for earth reconnaissance and the collection of scientific data (Watts et al., 2012). Additionally, the study emphasizes some of the advantages and benefits of these systems, such as increased mission safety, extended flight duration, and decreased operational costs. These are also consistent with the findings of Gupta et al.'s (2013) study. These two studies demonstrate that UAS systems are valuable for both military and civilian applications and have, therefore, had a significant positive impact on the American economy. This study contributes to the current analysis because it demonstrates that the removal of these systems from the market will have repercussions for both security and civilians. There will be challenges with scientific research and remote sensing that may have an effect on the general advancement of the scientific disciplines. Understanding the use and significance of these systems will make it simpler to comprehend the effects of their removal from use by state and local agencies. These actors use the UAS for more than just security, so removing them from the market would impact more than just the security applications of the systems.
Mohsan et al.'s (2022) study on the applications of UAVs revealed additional uses for drones, including military, construction, image and video imaging, search and rescue, and exploration. According to Mohsan et al. (2022), these have advantages for state and local agencies, including access to remote and disaster-stricken areas and cost efficacy. The research also indicates constraints such as low battery endurance, flight time, and autonomy. These limitations are constant across investigations, suggesting that these systems have been ineffective. This information is relevant and useful to the current study because it enables local and state authorities to design better strategies to overcome these restrictions. This might have a positive effect on the prohibition and allow the actors to surpass what is now available on the American market.
Ponchak et al. (2016) undertook research to assess the practicality of "point-to-point" (PTP) and "Network" methods to UAS development. The study sought to examine potential evolutionary paths for increasing UAS output. Ponchak et al. (2016) discovered that both ways to constructing UAS are practical, albeit the PTP approach is more easier to implement and run. However, the strategy is less scalable and more vulnerable to inference. The network strategy is more scalable, but it is more complex to put in place. Ponchak et al. (2016) concluded that the network method is appropriate for large-scale UAS operations while the PTP technique is appropriate for small-scale operations. The findings of this study are relevant to the current study because they show numerous techniques that American agencies might apply in the development of UAS systems. With the removal of Chinese UAS, the US now has the chance to create its own comparable systems, and this information might be beneficial in the development of those systems.
The research under consideration highlights the applicability, benefits, limits, and composition of UAS systems. They show how UAS systems have been applied by US government entities. This research is a good resource for understanding the impact of Chinese UAS withdrawal from usage by local and state agencies, as well as how the United States might negotiate this position in connection to the current study.
Review Methods
The primary source of data was FAA documents provided by the Massachusetts ACLU in May 2021. To ensure the validity of the study, the dataset was thoroughly examined to find any inconsistencies, outliers, or missing values. The dataset was cleaned to remove discrepancies, thereby keeping data integrity. Drones that lacked values for essential criteria like 'Manufacturing Country' were rectified, assuring the accuracy of the following analyses.
The analysis begins with the use of descriptive statistics to understand the basic structure of the dataset. This gave an overview of drone distribution based on 'Manufacturing Country,' providing insight into the proportion of Chinese drones deployed by state and local agencies in the state of Massachusetts compared to those from other countries. Because the data was categorical, especially factors such as 'Org Name,' 'City,' 'Zip Code,' and 'Manufacturing Country,' the chi-squared test was a suitable choice. It helped determine whether there was a substantial relationship between the nation of origin of the drones and the entities or places that used them. The chi-squared test's significance level (p-value) revealed if there were statistically significant connections. In summary, the quantitative method was predicated on a meticulous approach to cleansing data and rigorous statistical analysis, with the goal of providing a complete assessment of the possible implications of a Chinese UAS ban on Massachusetts state and local public safety organizations.
Results and Explanations
Table 1 shows a detailed analysis of drone distribution by the country of origin. China has 393 drones, accounting for the vast majority of the total 427 drones. This is around 92.04 percent of the overall drone population. On the other end of the spectrum, Canada has the fewest drones recorded in our dataset, with only three drones accounting for 0.70 percent of the total. France, despite likewise having a low participation, has a little higher presence with 10 drones, accounting for around 2.34% of the total. Drones manufactured in the United States account for around 4.92 percent of the overall number.
It is evident from these statistics that China dominates the drone manufacturing landscape in this dataset, with almost all other nations having a negligible presence. This preference for Chinese-made drones may be attributable to a variety of economic, technological, and geopolitical factors, such as China's competitive pricing, advanced technology, or strategic partnerships in the drone industry.
Table 2 reveals the same noteworthy pattern: the plurality of drones, 393 out of 427, are manufactured in China. Moving on to the Chi-square test results, we find a statistical value of 158.75669 with 159 degrees of freedom. Notably, the p-value of the test is 0.4905. The fact that this p-value is significantly higher than the typical significance threshold of 0.05 suggests that we cannot reject the null hypothesis. This suggests that there may not be a statistically significant correlation between the organization's name and the country in which their drones are manufactured. When comparing organizations, the origin of their drones (in terms of country of manufacture) does not appear to differ statistically significantly.
Conclusions/Interpretations
The research findings underscore the reliance of state and local governments on Chinese-made drones. Chinese manufacturers are responsible for an astounding 92.04 percent of the drones in the dataset pertaining to the state of Massachusetts. This is consistent with previous research that has highlighted China's dominant position in the global drone industry, which is frequently attributed to its competitive pricing, advanced technology, and strategic alliances.
Intriguingly, Gupta et al. (2013) and Mohsan et al. (2023) found that the reliance on and value of UAS systems in security, surveillance, and a variety of civilian applications are growing as a result. According to Watts et al. (2012), the proposed prohibition on Chinese drones could have significant implications, affecting not only security operations but also civilian applications such as scientific research, remote sensing, and earth-sensing reconnaissance. However, the chi-square test results indicate no statistically significant relationship between organizations and the country of drone production. This could suggest that the preference for Chinese-made drones is prevalent and not limited to a select few agencies. This trend suggests that the potential repercussions of the proposed moratorium would be widespread, uniformly affecting a diverse array of state and local entities.
Notably, while the existing literature emphasizes the operational benefits of UAS systems, it also emphasizes their inherent limitations, particularly battery endurance, flight duration constraints, and flight autonomy (Mohsan et al., 2022, 2023). These constraints do provide an opportunity. The study by Ponchak et al. (2016) suggests that in the event of a ban on Chinese UAS, there may be a renewed drive towards R&D to develop indigenous drones that surmount these limitations.
Considering the extensive use and benefits of UAS systems in the United States for security and civilian applications, the withdrawal of Chinese UAS systems would unquestionably result in a financial and operational vacuum. In conjunction with the existing literature, the findings suggest that a prompt and strategic response would be required to navigate such a scenario. In evaluating the decision on the proposed ban, policymakers must take into account not only the security implications but also the broader economic and operational implications for state and local agencies. In conclusion, while the results are consistent with prior research on the significance and applications of UAS systems, they also cast light on the predominance of Chinese drones in the current UAS landscape. The potential ban poses formidable obstacles but also presents opportunities for innovation, indigenous development, and reshaping the future of UAS technology in the United States.
References
Gupta, S. G., Ghonge, M., & Jawandhiya, P. M. (2013). Review of Unmanned Aircraft System (UAS). SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3451039
Mohsan, S. A., Khan, M. A., Noor, F., Ullah, I., & Alsharif, M. H. (2022). Towards the Unmanned Aerial Vehicles (UAVs): A comprehensive review. Drones, 6(6), 147. https://doi.org/10.3390/drones6060147
Mohsan, S. A., Othman, N. Q., Li, Y., Alsharif, M. H., & Khan, M. A. (2023). Unmanned Aerial Vehicles (UAVs): Practical aspects, applications, open challenges, security issues, and future trends. Intelligent Service Robotics. https://doi.org/10.1007/s11370-022-00452-4
Ponchak, D. S., Church, G., Auld, E., & Henriksen, S. (2016). A summary of two recent UAS Command and control (C2) communications feasibility studies. 2016 IEEE Aerospace Conference. https://doi.org/10.1109/aero.2016.7500666
Watts, A. C., Ambrosia, V. G., & Hinkley, E. A. (2012). Unmanned Aircraft Systems in remote sensing and scientific research: Classification and considerations of use. Remote Sensing, 4(6), 1671–1692. https://doi.org/10.3390/rs4061671
Appendix
Table 1: Frequency table results for Manufacturing Country
Canada | 3 | 0.0070257611 |
China | 393 | 0.92037471 |
France | 10 | 0.023419204 |
US | 21 | 0.049180328 |
Table 2: Contingency table results
Canada | China | France | US | Total | |
Ait/Massdot Aeronautics | 0 | 2 | 0 | 0 | 2 |
Amherst Fire Department | 0 | 2 | 0 | 0 | 2 |
Ayer Police Department | 0 | 1 | 0 | 0 | 1 |
Barnstable County Sheriff's Office | 0 | 4 | 0 | 4 | 8 |
Barnstable Police Department | 0 | 3 | 0 | 0 | 3 |
Berkshire County Sheriff's Office | 0 | 2 | 0 | 0 | 2 |
Boston Police Department Crime Scene Response Unit | 0 | 12 | 0 | 6 | 18 |
Bridgewater Police Department | 0 | 2 | 0 | 0 | 2 |
Central Massachusetts Regional Planning Commission | 0 | 4 | 0 | 0 | 4 |
City of Methuen | 0 | 3 | 0 | 0 | 3 |
City of Westfield, MA (Police) | 0 | 2 | 0 | 0 | 2 |
Department of Geography, Salem State University | 0 | 2 | 0 | 0 | 2 |
Duxbury Police Department | 0 | 2 | 0 | 0 | 2 |
Easthampton Police Department | 0 | 1 | 0 | 0 | 1 |
Fall River Police Department | 0 | 2 | 0 | 0 | 2 |
Franklin Police | 0 | 3 | 0 | 0 | 3 |
Ipswich Police Department | 0 | 2 | 0 | 0 | 2 |
Lanesborough Police | 0 | 1 | 0 | 0 | 1 |
Ma Environmental Police | 0 | 1 | 0 | 0 | 1 |
Manchester Police Department | 0 | 0 | 1 | 0 | 1 |
Marshfield Police | 0 | 2 | 0 | 0 | 2 |
Mass Department of Fire Services | 0 | 6 | 0 | 0 | 6 |
Massachusetts Dept of Transportation - Aeronautics Division Uas | 0 | 171 | 9 | 9 | 189 |
Massachusetts State Police | 3 | 78 | 0 | 0 | 81 |
Massachusetts Water Resources Authority | 0 | 4 | 0 | 0 | 4 |
Norfolk County Sheriff's Office | 0 | 1 | 0 | 0 | 1 |
North Brookfield Police Department | 0 | 1 | 0 | 0 | 1 |
Northampton Police | 0 | 16 | 0 | 0 | 16 |
Norton Fire Department | 0 | 1 | 0 | 0 | 1 |
Plainville Fire Dept. | 0 | 2 | 0 | 0 | 2 |
Quincy Police | 0 | 2 | 0 | 0 | 2 |
Southeastern Massachusetts Regional 911 District | 0 | 1 | 0 | 0 | 1 |
Springfield Fire Department | 0 | 3 | 0 | 0 | 3 |
Swansea Police Department | 0 | 3 | 0 | 0 | 3 |
Tewksbury Poice Department | 0 | 10 | 0 | 0 | 10 |
Town of Agawam, Agawam Fire Department | 0 | 4 | 0 | 0 | 4 |
Town of Chelmsford | 0 | 1 | 0 | 0 | 1 |
Town of Dennis | 0 | 2 | 0 | 0 | 2 |
Town of Huntington | 0 | 1 | 0 | 0 | 1 |
Town of Lynnfield | 0 | 1 | 0 | 0 | 1 |
Town of Natick | 0 | 1 | 0 | 0 | 1 |
Town of Southwick (Police) | 0 | 1 | 0 | 0 | 1 |
Town of Sudbury Police Department | 0 | 2 | 0 | 0 | 2 |
University of Massachusetts - Amherst | 0 | 2 | 0 | 0 | 2 |
University of Massachusetts Amherst | 0 | 5 | 0 | 0 | 5 |
University of Massachusetts Boston | 0 | 2 | 0 | 0 | 2 |
University of Massachusetts, Boston | 0 | 2 | 0 | 2 | 4 |
Usdot Volpe Center V315 | 0 | 1 | 0 | 0 | 1 |
Walpole Police Department | 0 | 1 | 0 | 0 | 1 |
Waltham Police Department | 0 | 10 | 0 | 0 | 10 |
Wayland Police | 0 | 2 | 0 | 0 | 2 |
Westfield State University | 0 | 1 | 0 | 0 | 1 |
Williamstown Police Department (Ma) | 0 | 1 | 0 | 0 | 1 |
Yarmouth Police Department | 0 | 1 | 0 | 0 | 1 |
Total | 3 | 393 | 10 | 21 | 427 |
Chi-Square test:
Statistic | DF | Value | P-value |
Chi-square | 159 | 158.75669 | 0.4905 |
Warning: Over 20% of cells have an expected count of less than 5.
Chi-Square suspect.