Future of Crime Solving – Artificial Intelligence Driven Nanotechnology

Authors

  • Gerard Pradeep Devnath S Assistant Professor, Department of Forensic Medicine and Toxicology, AIIMS, Madurai Author
  • Sanjay Gupta Professor & Head, Department of Forensic Medicine and Toxicology, AIIMS, Rajkot Author
  • Senthil Kumaran M Associate Professor, Department of Forensic Medicine and Toxicology, AIIMS, Madurai Author
  • Venkatesh Janarthanan Assistant Professor, Department of Forensic Medicine and Toxicology, AIIMS, Kalyani. Author
  • Aravindan U Senior Resident, Department of Forensic Medicine and Toxicology, AIIMS, Madurai Author

DOI:

https://doi.org/10.48165/jfmt.2026.43.02.19

Keywords:

Arrtificial Intelligence, Nanotechnology, Nanoscience, Forensic Investigation

Abstract

Artificial intelligence (AI) and nanotechnology are most hyped but also the least explored and understood. Forensic experts often face challenges in processing evidences in chaotic and complex environment using conventional techniques, leading to failure of investigation or miscarriage of justice. AI aids handling evidences effectively and analysing it to reach logical conclusions. Nanotechnology has an important advantage as it reveals hidden evidence, which can prove to be helpful to give accurate and unbiased results within a short period. Advances in AI are allowing us to understand the behaviour of materials at the nanoscale, and convergence between these two fields is enabling better data acquisition and improved crime-solving pattern.

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Author Biographies

  • Gerard Pradeep Devnath S, Assistant Professor, Department of Forensic Medicine and Toxicology, AIIMS, Madurai

    Assistant Professor, Department of Forensic Medicine and Toxicology

  • Sanjay Gupta, Professor & Head, Department of Forensic Medicine and Toxicology, AIIMS, Rajkot

    Professor & Head, Department of Forensic Medicine and Toxicology

  • Venkatesh Janarthanan, Assistant Professor, Department of Forensic Medicine and Toxicology, AIIMS, Kalyani.

    Assistant Professor, Department of Forensic Medicine and Toxicology

  • Aravindan U, Senior Resident, Department of Forensic Medicine and Toxicology, AIIMS, Madurai

    Senior Resident, Department of Forensic Medicine and Toxicology

References

Strekalova, Y. A. (Ed.). (2023). The role of digital health for strengthening health systems in low- and middle-income countries [Special issue]. International Journal of Environmental Research and Public Health, 20(1). https://www.mdpi.com/journal/ijerph/special_issues/digital_health_strengthen_health_system_LMIC

Paikrao, H. M., Tajane, D. S., Patil, A. S., & Dipale, A. D. (2021). Applications of nanotechnology in forensic science. In H. Sarma, S. Gupta, M. Narayan, R. Prasad, & A. Krishnan (Eds.), Engineered nanomaterials for innovative therapies and biomedicine (Nanotechnology in the Life Sciences, pp. 257–276). Springer.

Kumar, N., & Sharma, A. (2021). Nano-forensics: The new perspective in precision forensic science. In H. Sarma, S. Gupta, M. Narayan, R. Prasad, & A. Krishnan (Eds.), Engineered nanomaterials for innovative therapies and biomedicine (Nanotechnology in the Life Sciences, pp. 111–134). Springer.

Mangrulkar, A., Rane, S. B., & Sunnapwar, V. (2021). Automated skull damage detection from assembled skull model using computer vision and machine learning. International Journal of Information Technology, 13, 1785–1790.

Tu, P., Book, R., Liu, X., Krahnstoever, N., Adrian, C., & Williams, P. (2007). Automatic face recognition from skeletal remains. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (Minneapolis, MN, USA, June 17–22, 2007).

Ramanathan, N., Chellappa, R., & Biswas, S. (2009). Age progression in human faces: A survey. Journal of Visual Languages & Computing, 15, 3349–3361.

Jarrett, A., & Choo, K. R. (2021). The impact of automation and artificial intelligence on digital forensics. WIREs Forensic Science, 3(6), e1418. https://doi.org/10.1002/wfs2.1418

Armanious, K., Abdulatif, S., Bhaktharaguttu, A. R., Küstner, T., Hepp, T., Gatidis, S., & Yang, B. (2021). Organ-based chronological age estimation based on 3D MRI scans. In Proceedings of the 28th European Signal Processing Conference (pp. 1225–1228).

Dot, G., Rafflenbeul, F., Arbotto, M., Gajny, L., Rouch, P., & Schouman, T. (2020). Accuracy and reliability of automatic three-dimensional cephalometric landmarking. International Journal of Oral and Maxillofacial Surgery, 49, 1367–1378.

Li, L., et al. (2020). Using artificial intelligence to detect COVID-19 and community-acquired pneumonia based on pulmonary CT: Evaluation of the diagnostic accuracy. Radiology, 296, E65–E71.

Sessa, F., et al. (2020). Clinical-forensic autopsy findings to defeat COVID-19 disease: A literature review. Journal of Clinical Medicine, 9, 2026. https://doi.org/10.3390/jcm9072026

Shamout, F. E., Shen, Y., Wu, N., et al. (2021). An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department. NPJ Digital Medicine, 4(1), 80. https://doi.org/10.1038/s41746-021-00453-0

Sessa, F., Esposito, M., Messina, G., Di Mizio, G., Di Nunno, N., & Salerno, M. (2021). Sudden death in adults: A practical flow chart for pathologist guidance. Healthcare, 9(7), 870. https://doi.org/10.3390/healthcare9070870

Porto, L. F., Lima, L. N., Franco, A., Pianto, D., Machado, C. E., & de Barros Vidal, F. (2020). Estimating sex and age from a face: A forensic approach using machine learning based on photo-anthropometric indexes of the Brazilian population. International Journal of Legal Medicine, 134, 2239–2259.

Ramanathan, N., Chellappa, R., & Biswas, S. (2009). Age progression in human faces: A survey. Journal of Visual Languages & Computing, 15, 3349–3361.

ERMProtect. (n.d.). Do the benefits of artificial intelligence outweigh the risks? https://ermprotect.com/blog/do-the-benefits-of-artificial-intelligence-outweigh-the-risks/

Lloyd-Hughes, H., et al. (2015). Current and future nanotechnology applications in the management of melanoma: A review. Journal of Nanomedicine & Nanotechnology, 6, 334.

Dennis, E., et al. (2015). Utilizing nanotechnology to combat malaria. Journal of Infectious Diseases & Therapy, 3, 229. https://doi.org/10.4172/2332-0877.1000229

Fahim, G. G., et al. (2015). Deferiprone as a potential treatment for neurodegeneration with brain iron accumulation. Journal of Forensic Toxicology & Pharmacology, 4, 2.

Shyma, M. S., Ansar, E. B., Gayathri, V., Varma, H. K., & Mohanan, P. V. (2015). Attenuation of cisplatin-induced toxicity by melatonin loaded on dextran-modified iron oxide nanoparticles: An in vitro study. Journal of Forensic Toxicology & Pharmacology, 4(2).

Yadav, S. K. (2015). Nanotechnology: A spark to the use of plant origin bioactive compounds in therapeutics. Single Cell Biology, 4, 108.

Nikalje, A. P. (2015). Nanotechnology and its applications in medicine. Medicinal Chemistry, 5, 81–89.

Syduzzaman, et al. (2015). Smart textiles and nano-technology: A general overview. Journal of Textile Science & Engineering, 5, 181.

Hadi, N. I., et al. (2012). Electrical conductivity of rocks and dominant charge carriers: The paradox of thermally activated positive holes. Journal of Earth Science & Climate Change, 3, 128.

Pooja, A., & Vyas, J. M. (2015). A developmental overview of voice as a steadfast identification technique. Journal of Forensic Research, 6, 282.

Soni, S. R., et al. (2015). Effect of demographic variables on organizational role stress and burnout: An empirical investigation. Journal of Psychiatry, 18, 233.

Rohatgi, R., & Dominica, F. (2000). Application of nanotechnology in forensic science. Journal of Forensic Research, 13(8), 507.

Devi, E. C., et al. (2016). Phytochemical analysis of Solanum virginianum and its effect on human pathogenic microbes with special emphasis on Salmonella typhi. Journal of Forensic Toxicology & Pharmacology, 5, 141.

Brode, B. (2022, March 21). AI and nanotechnology are working together to solve real-world problems. The Overflow. https://stackoverflow.blog/2022/03/21/ai-and-nanotechnology-are-working-together-to-solve-real-world-problems/

Published

2026-07-12

How to Cite

Devnath S, G. P., Gupta, S., Kumaran M, S., Janarthanan, V., & U, A. (2026). Future of Crime Solving – Artificial Intelligence Driven Nanotechnology. Journal of Forensic Medicine and Toxicology, 43(2), 121-124. https://doi.org/10.48165/jfmt.2026.43.02.19