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The Use of Drones and the New Procedural Safeguards in Crime Control and Criminal Investigation

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Investigating and Preventing Crime in the Digital Era

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Abstract

Drones have become of enormous practical usefulness for crime prevention and criminal investigation. The use of drones, indeed, contribute to the collection of a wide range of information and data that could convey crucial knowledge for criminal proceedings. However, considering the highly intrusive potential of such tools on people’s private lives, serious concerns arise within the perspective of fundamental rights. The purpose of this study is to analyse the potentialities of drones in a modern criminal justice system while examining whether and how their usage is compliant with the rights to privacy and data protection.

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Notes

  1. 1.

    On the potentialities of technological tools in law enforcement and criminal proceedings see Czerniawski and Boyack (2021); Camon (2021); Caianiello (2019).

  2. 2.

    Cf. Tarr et al. (2022); Langham (2021).

  3. 3.

    See International Civil Aviation Organization (2011), Unmanned Aircraft Systems (UAS), Cir. 328-An 190, Glossary, accessible at https://www.icao.int/meetings/uas/documents/circular%20328_en.pdf.

  4. 4.

    See widely Carr (2021), p. 186 ff.; Carr (2019); Howell (2018); Meola (2017); Takahashi (2012); Ukman (2012).

  5. 5.

    Cf. Carr (2021), p. 186: the author stresses that “the basic drones can fly for up to 10 min on a battery charge at up to 22 mph, with a range about 150–200 feet”; see also Canis (2015), p. 5; see also Kaminski (2013); Anderson (2012).

  6. 6.

    Carr (2021), p. 186.

  7. 7.

    See widely Engberts and Gillissen (2016), p. 93 ff.

  8. 8.

    Federal Aviation Administration (2018) FAA AEROSPACE FORECAST: Fiscal Years 2018–2038, pp. 41–43.

  9. 9.

    Cf. Canis (2015), p. 11; Bond (2015).

  10. 10.

    See Alamouri et al. (2021), p. 8.

  11. 11.

    Federal Aviation Administration Modernization and Reform Act of 2012, sec. 336 (c); Code of Federal Regulation, title 14, para. 107.31.

  12. 12.

    Federal Aviation Administration Modernization and Reform Act of 2012, sec. 334; Code of Federal Regulation, title 14, para. 107.51. Decker (2017), p. 90, pointed out that “beyond this, the FAA has not made any specific attempt to regulate the use of drones by law enforcement, leaving such issues to state and federal legislators”.

  13. 13.

    Federal Aviation Administration, Part 107 Waiver, accessible at https://www.faa.gov/uas/commercial_operators/part_107_waivers/.

  14. 14.

    See Regulation (EU) 2018/1139, followed by Delegated Regulation (EU) 2019/945 and Implementing Regulation (EU) 2019/947. First, the ‘open’ category covers operations presenting the lowest risks. The main advantage of this category is that drone operators do not need an operating permit to fly their UAVs. Second, the ‘specific’ category includes other type of operations presenting a higher risk during the flight in relation to which a thorough risk assessment should be conducted to indicate which requirements are necessary to keep the operation safe. These operations, moreover, necessitate an operating license, based on a performed risk assessment reviewed by the competent authority. Third, the ‘certified’ category covers cases of high-risk activities, such as flying over assemblies of people, transporting people, and carrying dangerous goods. Cf. Alamouri et al. (2021), p. 4 ff.; Bajáková (2021); Clothier and Walker (2015).

  15. 15.

    Cf. Alamouri et al. (2021), p. 8: “VLOS is particularly interpreted to mean up to 500 m horizontally and 120 m vertically, but for large and well-visible systems (striking painting, position lights), altitudes up to 1000 or even 1500 m, and a radius of 1.5 km around the operator, have been accepted as VLOS”.

  16. 16.

    Id., p. 9.

  17. 17.

    European Union Aviation Safety Agency (2019) Acceptable Means of Compliance (AMC) and Guidance Material (GM) to Commission Implementing Regulation (EU) 2019/947, p. 11, accessible at https://www.easa.europa.eu/downloads/104072/en.

  18. 18.

    See Bump (2019); Rivello (2018); Bachmaier Winter (2014).

  19. 19.

    Cf. Engberts, Gillissen (2016), p. 93 ff. Consider, for example, the 2013 Boston Marathon bombing case. McNeal (2014), p. 3, stressed that “a marathon is the type of event where the police would want to use a drone to monitor for unknown attackers, and in the unfortunate event of an attack, use the footage to identify the perpetrators”.

  20. 20.

    See Boštjan (2016), p. 12.

  21. 21.

    Cf. Quattrocolo (2020), p. 39.

  22. 22.

    Rosenberg (2020).

  23. 23.

    Ibid.

  24. 24.

    Ibid.

  25. 25.

    Tarr et al. (2022).

  26. 26.

    Cf. Mendis et al. (2017); Mishra et al. (2015).

  27. 27.

    Ibid.

  28. 28.

    Mendis et al. (2017).

  29. 29.

    According to American Geoscience Institute LiDAR technology uses light in the form of a pulsed laser to measure an object’s variable distance from the Earth. These light pulses generate precise, three-dimensional information about the shape of the Earth and the target object. Accessible at https://www.americangeosciences.org/critical-issues/faq/what-lidar-and-what-it-used.

  30. 30.

    See Boštjan (2016), p. 11.

  31. 31.

    Mishra et al. (2015).

  32. 32.

    Conference of the Parties to the United Nation Convention against Transnational Organized Crime (2020), CTOC/COP/2020/L.7/Rev. 1, Vienna, recital no. 12, in https://www.unodc.org/documents/treaties/UNTOC/COP/SESSION_10/Resolutions/Resolution_10_4_-_English.pdf.

  33. 33.

    United Nations Office on Drugs and Crime (2012) Digest of organized crime cases. A compilation of cases with commentaries and lessons learned. New York, p. 45, accessible https://www.unodc.org/unodc/en/organized-crime/digest-of-organized-crime-cases.html.

  34. 34.

    Cf. Boštjan (2016), p. 12.

  35. 35.

    See widely on this theme Barfield and Pagallo (2020); Raul (2019); Schünemann and Baumann (2017); Tzanou (2017); Pagallo (2014); Belfiore (2013).

  36. 36.

    Cf. Pollicino (2021), p. 105; Mitsilegas (2009), p. 276; Gutwirth and De Hert (2008), p. 278 ff.

  37. 37.

    See ECtHR, Big Brother Watch v. United Kingdom, judgment of 13 September 2018, Appl. No. 58170/13. On this judgment see Bachmaier Winter (2021). See also, ECtHR, Zakharov v. Russia, judgment of 4 December 2015, Appl. No. 47143/06.

  38. 38.

    See ECtHR, Siliadin v. France, judgment of 26 July 2005, Appl. No. 73316/01; ECtHR, M.C. v. Bulgaria, judgment of 4 December 2003, Appl. No. 39272/98; ECtHR, Kokkinakis v. Greece, judgment of 25 May 1993, Appl. No. 14307/88; ECtHR, Huvig v. France, judgement of 24 April 1990, Appl. No. 11105/84. See also De Hert and Malgieri (2020).

  39. 39.

    ECtHR, S. and Marper v. The United Kingdom, judgment of 4 December 2008, Appls. Nos. 30,562/04 and 30,566/04, para. 112.

  40. 40.

    See Article 8(2) ECHR.

  41. 41.

    Cf. Barfield and Pagallo (2020); Quattrocolo (2020); Brkan (2018); Belfiore (2013), p. 355 ff.

  42. 42.

    Article 52(3) ChFREU establishes that “in so far as this Charter contains rights which correspond to rights guaranteed by the Convention for the Protection of Human Rights and Fundamental Freedoms, the meaning and scope of those rights shall be the same as those laid down by the said Convention”.

  43. 43.

    Article 29 Data Protection Working Party (2015) Opinion 01/2015 on “Privacy and Data Protection Issues relating to the Utilisation of Drones”, 01673/15/EN, WP 231, Brussels, 16 June 2015, accessible at https://ec.europa.eu/newsroom/article29/items/640602. See also Covino (2018), p. 267 ff.

  44. 44.

    Article 29 Data Protection Working Party (2015), p. 11.

  45. 45.

    Ibid.

  46. 46.

    European Data Protection Supervisor (2017) Assessing the Necessity of Measures That Limit the Fundamental Right to the Protection of Personal Data: A Toolkit, p. 5, accessible at https://edps.europa.eu/sites/edp/files/publication/17-04-11_necessity_toolkit_en_0.pdf.

  47. 47.

    See Barfield and Pagallo (2020); Ubertis (2020), p. 7; Leenes et al. (2017); Merla (2016); Klitou (2014).

  48. 48.

    Barfield, Pagallo (2020).

  49. 49.

    According to Article 4(5) GDPR “pseudonymisation means the processing of personal data in such a manner that the personal data can no longer be attributed to a specific data subject without the use of additional information, provided that such additional information is kept separately and is subject to technical and organisational measures to ensure that the personal data are not attributed to an identified or identifiable natural person”.

  50. 50.

    Adapted from Article 25(1) GDPR.

  51. 51.

    Cf. Article 25(2) GDPR.

  52. 52.

    Proposal for a Regulation of the European Parliament and of the Council Laying Down Harmonised Rules on Artificial Intelligence (Artificial Intelligence Act) and Amending Certain Union Legislative Acts, Brussels, COM(2021)206 final.

  53. 53.

    See widely in this volume Neroni Rezende, para. 2.

  54. 54.

    Cf. Article 5(2) of the Proposal.

  55. 55.

    Ibid.

  56. 56.

    See widely Langham (2021); McNeal (2014); Celso (2014); Villasenor (2013); Olivito (2013); Takahashi (2012); Calo (2011).

  57. 57.

    U.S. Const. Amend. IV.

  58. 58.

    Langham (2021), p. 71; see also Celso (2014); McNeal (2014); Takahashi (2012).

  59. 59.

    See in this volume Di Nuzzo.

  60. 60.

    Carrol v. United States, 267 U.S. 132 (1925); Olmstead v. United States, 277 U.S. 438 (1928); Silverman v. United States, 365 U.S. 505 (1961); Hayden v. United States, 387 U.S. 294 (1967); Katz v. United States, 389 U.S. 347 (1967).

  61. 61.

    Katz v. United States, 389 U.S., para. 359.

  62. 62.

    Id., para. 359; see also Osborn v. United States, 385 U.S. 323 (1996), para. 330.

  63. 63.

    Katz v. United States, 389 U.S., para. 359.

  64. 64.

    Id., para. 361, (Harlan J concurring opinion).

  65. 65.

    See California v. Ciraolo, 476 U.S. 207 (1986), paras. 208–209.

  66. 66.

    Id., para. 209.

  67. 67.

    Id., paras. 211–215; see also Dow Chemical Co. v. United States, 476 U.S. 227 (1986), in which the Court held that “the use of an aerial mapping camera to photograph an industrial manufacturing complex from navigable airspace similarly does not require a warrant under the Fourth Amendment”.

  68. 68.

    Kyllo v. United States, 533 U.S. 27 (2001), paras. 33–34.

  69. 69.

    Id., para. 40.

  70. 70.

    United States v. Jones, 565 U.S. 400 (2012); Riley v. California, 573 U.S. 373 (2014).

  71. 71.

    See widely Militello in this volume.

  72. 72.

    United States v. Jones, 565 U.S., paras. 414–415 (Sotomayor J concurring opinion).

  73. 73.

    Id., paras. 430–431 (Alito J concurring opinion).

  74. 74.

    Riley v. California, 573 U.S., para. 386.

  75. 75.

    Langham (2021), p. 92.

  76. 76.

    Carr (2021), p. 201; McGee, Stacey (2020).

  77. 77.

    See widely Fardo (2020).

  78. 78.

    European Data Protection Board (2020) Statement on the processing data in the context of the Covid-19 outbreak. Brussels, accessible at https://edpb.europa.eu/news/news/2020/statement-processing-personal-data-context-covid-19-outbreak_en.

  79. 79.

    Ibid.

  80. 80.

    Triggiani (2019), p. 186 ff.

  81. 81.

    Commission nationale de l'informatique et des libertés (2021) Délibération de la formation restreinte n°SAN-2021-003 du 12 janvier 2021 concernant le ministère de l'intérieur, https://www.legifrance.gouv.fr/cnil/id/CNILTEXT000042960768.

  82. 82.

    Id., para. 44.

  83. 83.

    Cf. Iorio (2021); Naddeo (2021).

  84. 84.

    Takahashi (2012), p. 113.

  85. 85.

    Koops (2006), p. 77 ff.

  86. 86.

    See widely Leenes et al. (2017); Leenes and Lucivero (2014); Koops and Leenes (2014); Leenes (2011); Brownsword (2008); Zaccagnino et al. (2021), p. 15804: “An example of techno-regulation can be seen in Digital Right Management systems, which incorporate copyright law into technological safeguards by limiting the use of copyrighted artifacts”.

  87. 87.

    Van den Berg and Leenes (2013).

  88. 88.

    Leenes et al. (2017), p. 29; Rosenberg (2020); Koops and Leenes (2006); Robolaw (2014) Guidelines on Regulating Robotics. Regulating Emerging Robotic Technologies in Europe: Robotics Facing Law and Ethics, accessible at http://www.robolaw.eu/RoboLaw_files/documents/robolaw_d6.2_guidelinesregulatingrobotics_20140922.pdf.

  89. 89.

    Leenes et al. (2017), p. 28: the Authors stress that “this not only implies that designers will have to build technologies capable of operating within these constraints, but also that certain kinds of robots will have to be able to ‘reason’ explicitly with legal norms or at least to execute particular norms in particular circumstances”.

  90. 90.

    Id., p. 27.

  91. 91.

    Koops and Leenes (2014), p. 159 ff.

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    Claudio Orlando

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Orlando, C. (2022). The Use of Drones and the New Procedural Safeguards in Crime Control and Criminal Investigation. In: Bachmaier Winter, L., Ruggeri, S. (eds) Investigating and Preventing Crime in the Digital Era. Legal Studies in International, European and Comparative Criminal Law, vol 7. Springer, Cham. https://doi.org/10.1007/978-3-031-13952-9_5

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  • DOI: https://doi.org/10.1007/978-3-031-13952-9_5

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