The Laboratory of Tomorrow: Automation, Robotics, and Innovation in Smart Forensic Science
Keywords:
Smart Forensic Laboratory, Laboratory Automation, Robotics, Artificial Intelligence (AI), Laboratory Information Management System (LIMS)Abstract
Traditional forensic labs are becoming smart lab, technology-driven labs and transforming the modern forensic science. The use of automation, robotics, artificial intelligence (AI), Laboratory Information Management Systems (LIMS), and digital technologies are improving the speed, accuracy, and reliability of forensic investigations and minimizing human effort and error. This review focuses on the transition of forensic laboratories from manual to integrated and automated processes and the role of robotic platforms, digital workflow management and intelligent forensic laboratory infrastructures. It also emphasizes on the use of smart technologies in Forensic Pathology, Digital Forensics, Biometrics, Crime scene investigation, Forensic chemistry and Forensic genetics. The review also looks at the key advantages and implementation constraints of smart forensic laboratories and forecasts future trends such as incorporation of artificial intelligence into robotics, Internet of Things (IoT) enabled monitoring, cloud data management, digital twins, and interoperable laboratory systems. The developments are expected to enhance the efficiency of the laboratory and also contribute to the scientifically sound and legally defensible forensic practices.
References
[1] Kloosterman et al., “The interface between forensic science and technology: how technology could cause a paradigm shift in the role of forensic institutes in the criminal justice system,” Philos. Trans. B, vol. 370, 2015, doi: http://dx.doi.org/10.1098/rstb.2014.0264.
[1] C. Omari, S. V. Manyele, and G. Mwaluko, “Analysis of Stress Backlogs during Case-File Processing in Forensic Science Laboratory,” Engineering, vol. 9, pp. 1060–1096, 2017, doi: https://doi.org/10.4236/eng.2017.912063.
[2] K. Thurow, O. Peter, P. Courtney, K. Széll, and Á. Wolf, “Editorial: Robotics in laboratory automation,” SLAS Technol., vol. 36, p. 100373, 2026, doi: https://doi.org/10.1016/j.slast.2025.100373.
[3] Asquith and G. Horsman, “Let the robots do it! – Taking a look at Robotic Process Automation and its potential application in digital forensics,” Forensic Sci. Int. Reports, vol. 1, p. 100007, 2019, doi: http://doi.org/10.1016/j.fsir.2019.100007.
[4] Opalinski, K. Regulski, J. Swadzba, P. W˛asowicz, A. Kwietniewska-Smietana, and P. Sitkowski, “Optimizing Laboratory Workflow Through Prediction of Test Demand and Quality Control,” Appl. Sci., vol. 16, no. 4865, pp. 1–17, 2026, doi: https://doi.org/10.3390/app16104865.
[5] X. Chango, O. Flor-unda, P. Gil-jiménez, and H. Gómez-moreno, “Technology in Forensic Sciences: Innovation and Precision,” Technologies, vol. 12, no. 120, 2024, doi: https://doi.org/10.3390/technologies12080120.
[6] M. L. Comeaga, “Digital transformation of the laboratories,” IOP Conf. Ser. Mater. Sci. Eng., 2022, doi: 10.1088/1757-899X/1268/1/012001.
[7] S. Bakyt, A. Zhanibekov, A. Paridinova, Y. Karzhaubayev, And N. Poshanov, “Application of AI capabilities in forensics and criminal proceedings: Innovative technologies in forensic examinations,” Oñati Int. Inst. Sociol. Law Avenida Univ., pp. 1–23, 2026, doi: HTTPS://DOI.ORG/10.35295/OSLS.IISL.2555.
[8] Y. Hailu, G. A. Mitiku, D. W. Seboka, and M. A. Gobena, “Advancing Forensic Science through Artificial Intelligence: A Systematic Review,” Ethiop. J. Police Stud., vol. 1, no. Ii, pp. 1–22, 2026, doi: https://doi.org/10.20372/ejpos.v1iII.12989.
[9] Magherescu, “Challenges of the forensic science facing new technologies,” IUS Sci., vol. 7, no. 1, pp. 48–61, 2021, doi: https://dx.doi.org/10.12795/IETSCIENTIA.
[10] T. Handa, D. P. Chakraborty, D. G. Kaur, D. A. Verma, and D. P. Arora, “Shaping the Future of Forensic Science by Smart Technology,” INDIAN J. Soc. Stud. Humanit., vol. 1, no. 17, pp. 1–8, 2024.
[11] R. M. Montgomery, “Augmenting Forensic Science Through AI: The Next Leap in Multidisciplinary Approaches,” Preprints, pp. 0–9, 2025, doi: 10.20944/preprints202501 .1951 .v1.
[12] N. Banagar and R. Khattar, “IoT based Smart Laboratory System,” Int. J. Eng. Res. Technol., vol. 9, no. 01, pp. 315–318, 2020, doi: 10.17577/IJERTV9IS010178.
