A Preliminary Study and Implementing Algorithm Using Finite State Automaton for Remote Identification of Drones

Round 1

Reviewer 1 Report

In this paper, Authors introduce a new ER-ID algorithm to make the LPN detection process of drones complete in an infinite range. However, the author does not give theoretical analysis and experimental proof. This is a relatively low contribution to the research community. My comments/questions are listed as follows.

1. In order to reflect the innovation of the article, Authors should carry out experiments to prove it.

2. Authors should further explain the process for connecting to a required RF-CS.

3. In Section 4.1, Authors states that the selection of RF communication signal is mainly determined by distance and energy consumption, but in Section 5, the factor of distance is not taken into account.

4. Abbreviations that first appear in the article should be explained, such as RF-CS on line 29.

Author Response

Reviewer #1:

Reply: We appreciate your valuable and relevant comments. There are several focal points in our study that we believe can be consolidated.

Comments and Suggestions for Authors

In this paper, Authors introduce a new ER-ID algorithm to make the LPN detection process of drones complete in an infinite range. However, the author does not give theoretical analysis and experimental proof. This is a relatively low contribution to the research community. My comments/questions are listed as follows.

 

1. In order to reflect the innovation of the article, Authors should carry out experiments to prove it.

Dear reviewer, in this paper we focused on the theory of increasing the remote identification range of drones by using Finite State Automaton. Therefore, the experiments are suggested in the conclusion section as a future work. Please see line (558-560) in the revised manuscript.

As a future work, it is recommended to practically implement the developed Finite state algorithm of this study.

2. Authors should further explain the process for connecting to a required RF-CS.

Thank you for this comment. In the revised manuscript, we explained now the process for connecting to a required RF-CS. Please see line (241-272) in the revised manuscript.

A GPRS modem enables a drone to establish a connection to a 4G or 5G network. This GPRS modem is then linked to the computer that is housed on the drone, such as a Raspberry Pi. For example, the drone is equipped with a GPRS modem that is attached to the onboard computer of the drone. This modem allows the drone to connect to 4G and 5G networks. When the central computer is ready to utilize the 4G/5G network, it sends a command to the GPRS modem, instructing it to deliver the electronic ID of the drone. During this time, the computer is performing the algorithm that was generated by the state machine. In terms of ADSB, the drone is outfitted with a modem designed specifically for use with drones (similar to the one DJI uses for some of his drones' ADSB out). As an example, drones that are located in close proximity to airports are required to broadcast their location to adjacent civilian aircraft. Additionally, drones must utilize ADSB out to convey their electronic identification and ADSB data. From the point of IoT, the drone has a specific long range IoT device (such as for example lora or sigfox), which may be linked at will to the lora network or the sigfox IoT network, or to the 6G IoT network. When the drone wishes to utilize IoT to communicate its electronic ID (in order to conserve energy since IoT is highly energy efficient), the drone will use its IoT modem. The instruction to communicate the information along with it is sent to the IoT device by the central computer of the drone. Subsequently, the IoT modem connects to the accessible IoT network and transmits the electronic ID. Due to the size of their modems, larger drones are an excellent candidate for this kind of satellite communication (Military drones already have a satellite modem fitted, enabling them to engage in real-time communication). When the drone is located in an isolated region or at a very high altitude, the need to utilize an RF-CS may be circumvented by employing satellite communications instead. The following is the procedure that must be followed in order to use satellite modems; When the central computer needs to send or receive data, it issues orders to the RF satellite modem. The RF satellite modem then reacts and begins to receive more commands from the central computer of the drone. Following this, the primary computer sends a command to the rf sat modem, instructing it to deliver the electronic ID. Drones are equipped with a Bluetooth device that allows them to connect to the local Bluetooth in mobile devices. Once connected, the drones are able to transmit their electronic identifiers to the internet via the mobile devices. Connecting to the relevant local aviation authority and transmitting its electronic id is accomplished by the drone via the use of the Rf communication method that is selected on an as-needed basis (GPRS, IoT, ADSB, satellite, bluetooth/WiFi). The authority in charge of aviation in the area is able to transmit orders to the drone if necessary.

3. In Section 4.1, Authors states that the selection of RF communication signal is mainly determined by distance and energy consumption, but in Section 5, the factor of distance is not taken into account.

Thank you for this comment. In section 4.1, the distance that we mentioned in term of kilometers was referred to the range as depicted in Figure 1. And this range is taken in consideration in our case study in section 5 and depicted it in Figure 4. In the revised manuscript we explained now in section 4.1 that as follow. Please see line (288-295) in the revised manuscript.

The range of RF-CSs, as explained in Table 1 and depicted in Figure 1, can be arranged in ascending manner as: Bluetooth (10 m), WiFi (200 m), 5G (1 km), IoT (15 km), 4G (16 km), ADS-B (200 km), and satellite (unlimited range). On the other hand, the RF-CSs can be arranged ascending manner in term of power as:  Bluetooth (1 mW), WiFi (50 mW), IoT (0.5 W), 4G (20 W), ADS-b (75W and 500 W), Satellite (230 W), and 5G (1-1.4 KW). These values including range and consumed energy should be taken in consideration during the transmission from one state to another during drone missions.

4. Abbreviations that first appear in the article should be explained, such as RF-CS on line 29.

Thank you. Addressed.

 

Reviewer 2 Report

My recommendation is to accept the paper

Comments for author File: Comments.pdf

Author Response

Reply: we appreciate the valuable and relevant comments provided by the reviewer #2. There are several focal points in our study that we believe are well consolidated. We completely agree with the reviewer's comments.

 

In this work, the authors introduce a new algorithm to the Electronic Remote Identification (ER-ID) such that the process of detecting LPN of drones can be done in limitless range. Also, the authors claimed that the new algorithm has increased the lifetime of the battery energy of the drone by developing a Finite State Automation (FSA) for transmitting the ER-ID data through Bluetooth, Wi-Fi, 4G/5G, ADS-B, long range IoT, and satellites.

 

Comments to the authors:

1- In the “Table_1”, do you think that the cost of each system is an important factor that should be taken into consideration? Please illustrate it with respect for each system.

 

Thank you for this comment. In the revised manuscript we mentioned and illustrated the costs of each system now. Please see line (204-212) in the revised manuscript.

According to table 1, the cost is significant only for satellite communications, particularly for person-viewing capabilities, but not for transmitting electronic identification. Many RF modems are already embedded in commercial drones, and the cost of adding a GPRS modem and IoT device is not a critical factor. Modern IoT devices, particularly within cities, can connect to both local smart cities IoT-deployed networks and satellites at low cost. Because many commercial devices use Bluetooth, RF modems for remote control, GNSS, and GPRS, the cost factor for the majority of these devices is already included.

Table 1

 

 

 

System name	Transmission rate	Drone Energy Consumption (mW)	Transmission Distance	Cost range (US $)
ADS-B	Up to 27 kbps	0.1	200 km	160-300
LoRaWan IoT	Up to 37.5 kbps	0.15	Up to 15 km	12-20
BlueTooth	Up to 24 Mbps	56.7	10 m	5-10
Wifi	Up 54 Mbps	58.1	50m indoors, 100m outdoors	2-10
4G	Up 300 Mbps	258.1	16 km	40-60
Satellite	Up to 500 Mbps for S-band.	283.1	From 400 km to 1000 km and inside the solar system	200-1000000
5G	Up 20 Gbps	463.1	Up to 1 km	50-70

 

2- In the “Case Study ” part, do you study the issue of Electromagnetic Compatibility (EMC) because the possible interaction between RFID tags themselves and other devices that use various forms of radio communication?

 

Thank for this comment. In the revised manuscript we mentioned now the of Electromagnetic Compatibility (EMC) between RFID. Please see line (536-540) in the revised manuscript.

Our suggested electronic ID would employ existing RF networks and solutions such as GPRS (4G/5G), IoT networks that have been installed in smart cities, established satellite communications, and local ADS-B RF modem networks that have been deployed by the local aviation authority. So, the drones will be able to use these RF solutions in the same way that already-working RF systems have solved all electromagnetic issues.

 

3- The authors developed their algorithm based on the open sky areas, however, there is no signs regarding the possibility of the drone to fly in a GNSS denied signal area like forest. Please illustrate this point carefully.

 

Thank you for this comment. In the revised manuscript we now illustrated this point carefully. Please see line (332-343) in the revised manuscript.

The electronic ID is a solution for RF communications and a method of identifying a drone to local aviation authorities, allowing them to send their electronic ID and receive information and possible commands from the local aviation authority. Because GNSS is used for GPS or Glonass to point an object in space and time, it is not supported by our electronic ID RF communication solution. It is true that drones use GNSS to control their flight, and that modern drones use it to locate themselves, but this is not required because drones use gyroscopes in conjunction with control algorithms and PID controllers to position themselves in space and time. As a result, GNSS is important but not required for an object to fly from point A to point B, just as rockets and drones have gyroscopes to fly from point A to point B if GNSS is unavailable. As a result, in areas such as forests where GNSS, GPRS, IoT, and ADS-B are unavailable, we rely on satellites to transmit electronic ID and gyroscopes to position ourselves in space and time.

Reviewer 3 Report

The article is written at a mediocre level, with a title indicating the presentation of Increased

Remote Identification Range of Drones by using Development Finite State Automaton, while

the content presents the theoretical applicability, without distinguishing the precise research

methodology, algorithms and formulas and the real confirmation of the assumptions made in

the research scenario. There is also a lack of quantitative indication of the research results,

related to energy demand and their comparison. It is suggested that supplementing the title

with "Feasibility study" will correctly identify the current content of the article and translate

into minor corrections to the text. If the title is retained, the article should absolutely be

supplemented with:

 details of the assumptions for the research scenario, related to UAV communication,

the formulas, algorithms and boundary conditions used,

 standardise the content of Table 1 with the description in the text (lines 253 - 256),

 reference to real scenarios, practical examples and energy requirements.

 

Independently of the above, a number of other comments have been identified for inclusion in

the article prior to publication:

1. The abbreviation RF-CS (line 29) was not developed..

2. The terms 'electronic R-ID' (e.g. line 57), 'ER-ID' (e.g. line 44, 50, 59) and 'R-ID' (e.g.

line 269, 277, 318) were used. The entries should be standardised or clearly

distinguished.

3. The abbreviation IEEE (line 110) has not been developed.

4. Double spaces occur in some places (you know 116, 123, 140, 213, 215, 238, 297,

341, 409).

5. The paragraph of section 2.3 "IoT Technology" has references to only two items

[33,34]. It is worth indicating more references.

6. No references to literature items are indicated for Table 1.

7. The units of energy should be standardised (line 255, 256) and used the same

throughout the article.

8. The values in rows 253 - 256 differ from the data in Table 1. the entries should be

harmonised.

9. Is there only one condition indicated in line 293 or are there more?

10. The text of section 4.3 'State Transition Diagram' has been formatted differently from

previous paragraphs.

11. The space in line 293 'RFcommunications' is missing

12. There is excessive space after line 307 which should be filled by reducing Figure 3.

13. Figure 3 should be completed with a legend.

14. Incorrect header formatting in line 374 - no bold or underline.

15. A different energy notation has been used in line 451 compared to other cases.

16. Incorrect formatting of header in line 463 - no bolding or underlining.

17. Unnecessary spacing in line 467.

18. According to Figure 3 the communication for points 44 - 45 is via satellite, not ADS-

B.

19. No quantification of the sum of the results.

Author Response

Reply: we appreciate the valuable and relevant comments provided by the reviewer #3. There are several focal points in our study that we believe are well consolidated.

 

The article is written at a mediocre level, with a title indicating the presentation of Increased Remote Identification Range of Drones by using Development Finite State Automaton, while the content presents the theoretical applicability, without distinguishing the precise research methodology, algorithms and formulas and the real confirmation of the assumptions made in the research scenario. There is also a lack of quantitative indication of the research results, related to energy demand and their comparison. It is suggested that supplementing the title with "Feasibility study" will correctly identify the current content of the article and translate into minor corrections to the text. If the title is retained, the article should absolutely be supplemented with:

• details of the assumptions for the research scenario, related to UAV communication, the formulas, algorithms and boundary conditions used
• standardise the content of Table 1 with the description in the text (lines 253 - 256),
• reference to real scenarios, practical examples and energy requirements.

Thank you for this comment. We have modified the title of the paper to be more general because we didn’t apply mathematical equations in this paper. In this study, we focused on implementing an algorithm using Finite state automaton to detect drones by all types of the available Radio Frequency Communication Systems with minimizing the consumed energy. Consequently, we changed the title of the paper to:

“A preliminary study and Implementing Algorithm Using Finite State Automaton for Drones Remote Identification “

 

Independently of the above, a number of other comments have been identified for inclusion in the article prior to publication:

1. The abbreviation RF-CS (line 29) was not developed.

Addressed.

2. The terms ' electronic R-ID' (e.g. line 57), 'ER-ID' (e.g. line 44, 50, 59) and 'R-ID' (e.g.line 269, 277, 318) were used. The entries should be standardised or clearly distinguished.

Addressed.

3. The abbreviation IEEE (line 110) has not been developed.

Addressed.

4. Double spaces occur in some places (you know 116, 123, 140, 213, 215, 238, 297, 341, 409).

Addressed.

5. The paragraph of section 2.3 "IoT Technology" has references to only two items [33,34]. It is worth indicating more references.

Thank you for this comment. The following references are added to section 2.3.

[35] Senadeera, S.D.A.P.; Kyi, S.; Sirisung, T.; Pongsupan, W.; Taparugssanagorn, A.; Dailey, M.N.; Wai, T.A. Cost-Effective and Low Power IoT-Based Paper Supply Monitoring System: An Application Modeling Approach. J. Low Power Electron. Appl. 2021, 11, 46. https://doi.org/10.3390/jlpea11040046

[36] J. Henkel, S. Pagani, H. Amrouch, L. Bauer and F. Samie, "Ultra-low power and dependability for IoT devices (Invited paper for IoT technologies)," Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017, Lausanne, Switzerland, 2017, pp. 954-959, doi: 10.23919/DATE.2017.7927129.

[37] U. Noreen, A. Bounceur and L. Clavier, "A study of LoRa low power and wide area network technology," 2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP), Fez, Morocco, 2017, pp. 1-6, doi: 10.1109/ATSIP.2017.8075570.

 

6. No references to literature items are indicated for Table 1.

Addressed. In the revised manuscript we added now the following references to literature items are indicated for Table 1.

[54] “ADS-B Technology | Drone Tracking Transponders| ADS-B Receivers.” Unmanned Systems Technology, 20 Jan. 2023, www.unmannedsystemstechnology.com/company/aerobits.

[55] Casals Ibáñez, Lluis & Mir Masnou, Bernat & Vidal Ferré, Rafael & Gomez, Carles. (2017). Modeling the energy performance of LoRaWAN. Sensors. 17. 2364. 10.3390/s17102364.

[56] “What Is LoRaWAN&Reg; Specification - LoRa Alliance®.” LoRa Alliance®, hz1.37b.myftpupload.com/about-lorawan. Accessed 21 Jan. 2023.

[57] “LoRa and LoRaWAN: Technical Overview | DEVELOPER PORTAL.” LoRa and LoRaWAN: Technical Overview | DEVELOPER PORTAL, /documentation/tech-papers-and-guides/lora-and-lorawan. Accessed 21 Jan. 2023.

[58] “Understanding Bluetooth Range | Bluetooth® Technology Website.” Bluetooth® Technology Website, www.bluetooth.com/learn-about-bluetooth/key-attributes/range. Accessed 21 Jan. 2023.

[59] Tsira, Vikethozo & Nandi, Gypsy. (2014). Bluetooth Technology: Security Issues and Its Prevention. International Journal of Computer Technology & Applications. 5. 1833.

[60] “What Is the Range of a Typical Wi-Fi Network?” Lifewire, 5 Nov. 2020, www.lifewire.com/range-of-typical-wifi-network-816564.

[61] Rishu Bhatia, 2015, Introduction & Features of 4G: A Review, INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH & TECHNOLOGY (IJERT) NCETEMS – 2015 (Volume 3 – Issue 10)

[62] Zou, Longhao & Javed, Ali & Muntean, Gabriel-Miro. (2017). Smart mobile device power consumption measurement for video streaming in wireless environments: WiFi vs. LTE. 1-6. 10.1109/BMSB.2017.7986151.

[63] A/S, Satlab. “SRS-3 Full-duplex S-band Transceiver.” SRS-3 Full-duplex S-band Transceiver, www.satlab.com/products/srs-3. Accessed 21 Jan. 2023.

[64] “5G Speed Vs 5G range-What Is the Value of 5G Speed,5G Range.” 5G Speed Vs 5G range-What Is the Value of 5G Speed,5G Range, www.rfwireless-world.com/Terminology/5G-Speed-Vs-5G-Range.html. Accessed 21 Jan. 2023.

7. The units of energy should be standardised (line 255, 256) and used the same throughout the article.

Addressed. The units of energy are standardised now to “mW” throughout the article.

8. The values in rows 253 - 256 differ from the data in Table 1. the entries should be harmonised.

Addressed. All the values in rows 253 – 256 are harmonized now with table 1. Please see line (288-295) in the revised manuscript.

 

The range of RF-CSs, as explained in Table 1 and depicted in Figure 1, can be arranged in ascending manner as: Bluetooth (10 m), WiFi (50 m indoors, 100 m outdoors), 5G (Up to 1000 m), IoT (Up to 15000 m), 4G (16000 m), ADS-B (200000 m), and satellite (From 400000 m to 1000000 km). On the other hand, the RF-CSs can be arranged ascending manner in term of power as:  ADS-b (0.1 mW), IoT (0.15 mW), Bluetooth (56.7 mW), WiFi (58 mW), 4G (258.1 mW), satellite (283.1 mW), and 5G (463.1 mW). These values including range and consumed energy should be taken in consideration during the transmission from one state to another during drone missions.

9. Is there only one condition indicated in line 293 or are there more?

We are mentioned about many conditions that determined the identification of drone as follows:

In ER-ID of drones, the conditions that determine the identification of drone are complex and include sub-regions, multi-RF-CSs, battery energy, response time of detecting RF signals, availability of RFcommunications signal, possible local country aviation authority regulations, ADS-B readings from other aircrafts and other drones, local restrictions of fly due to events, geofencing, and local airports.

10. The text of section 4.3 'State Transition Diagram' has been formatted differently from previous paragraphs.

Addressed

11. The space in line 293 'RFcommunications' is missing

Addressed

12. There is excessive space after line 307 which should be filled by reducing Figure 3.

Addressed.

13. Figure 3 should be completed with a legend.

Addressed. Please see Figure 3 in the revised manuscript.

14. Incorrect header formatting in line 374 - no bold or underline.

Addressed

15. A different energy notation has been used in line 451 compared to other cases.

Addressed

16. Incorrect formatting of header in line 463 - no bolding or underlining.

Addressed

17. Unnecessary spacing in line 467.

Addressed

18. According to Figure 3 the communication for points 44 - 45 is via satellite, not ADS-B.

Thank you for this comment. Addressed

19. No quantification of the sum of the results.

We added now the total consumed energy during the path scenario of the case study.

During the drone path scenario of this case study, the drone consumed only 2657.4681 mW.

Round 2

Reviewer 3 Report

The article has been revised and supplemented with the indicated comments. The present standard of the article is high and there are no defects that need to be corrected before publication.