Artificial Intelligence: An Advanced Evolution In Forensic and Criminal
Investigation

Yadav, Saurav; Yadav, Shalini S.; Verma, Preeti; Ojha, Smriti; Mishra, Sudhanshu

doi:10.2174/2666484401666220819111603

Cited by 5 publications

(4 citation statements)

References 20 publications

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“…Moving forward with MPS will allow the forensic community to continue using millions of DNA profiles that are currently stored in DNA databases, while also expanding its use of forensic DNA typing with increased genetic diversity in STR and SNP. Continued advances in AI are likely to play a crucial role in solving crimes and promoting justice in the future [40,81].…”

Section: Discussionmentioning

confidence: 99%

Artificial Intelligence and Forensic Genetics: Current Applications and Future Perspectives

Sessa,

Esposito,

Cocimano

et al. 2024

Applied Sciences

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The term artificial intelligence (AI) was coined in the 1950s and it has successfully made its way into different fields of medicine. Forensic sciences and AI are increasingly intersecting fields that hold tremendous potential for solving complex criminal investigations. Considering the great evolution in the technologies applied to forensic genetics, this literature review aims to explore the existing body of research that investigates the application of AI in the field of forensic genetics. Scopus and Web of Science were searched: after an accurate evaluation, 12 articles were included in the present systematic review. The application of AI in the field of forensic genetics has predominantly focused on two aspects. Firstly, several studies have investigated the use of AI in haplogroup analysis to enhance and expedite the classification process of DNA samples. Secondly, other research groups have utilized AI to analyze short tandem repeat (STR) profiles, thereby minimizing the risk of misinterpretation. While AI has proven to be highly useful in forensic genetics, further improvements are needed before using these applications in real cases. The main challenge lies in the communication gap between forensic experts: as AI continues to advance, the collaboration between forensic sciences and AI presents immense potential for transforming investigative practices, enabling quicker and more precise case resolutions.

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Section: Discussionmentioning

confidence: 99%

Artificial Intelligence and Forensic Genetics: Current Applications and Future Perspectives

Sessa,

Esposito,

Cocimano

et al. 2024

Applied Sciences

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“…14 Yadav et al (2020) conducted a forensic examination of cheap liquor in Karnataka, revealing high unrecorded alcohol consumption rates, particularly among males, leading to dangerous health consequences. 15 Caroline Magut (2020) studied illicit alcohol consumption among youth in Kenya, highlighting the prevalence of harmful liquor like Changaa and its adverse social and health effects. 16 Nikoo et al (2020) focused on the adulteration of liquor, emphasizing the presence of impurities and additives that can lead to severe health problems, including methanol-related blindness and death.…”

Section: Introductionmentioning

confidence: 99%

Forensic analysis of illicit liquors in Himachal Pradesh: Assessing toxicity and composition for public health safety

Kaur,

Thakur,

Mukherjee

et al. 2024

IJFCM

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Illicit liquors, also known as illegal, hooch, or bootleg liquors, refer to alcoholic beverages that are produced, distributed, or retailed in defiance of legal regulations and licensing requirements. These beverages are typically produced in clandestine operations, often circumventing taxation, quality control standards, and safety protocols mandated by authorities. The manufacture and consumption of illicit liquors present formidable hazards and complexities. Poisoning incidents linked to illicit liquors can result from contamination with hazardous substances, primarily methanol, alongside compounds such as esters, ketones, aldehydes, and acids, which can inflict deleterious effects on the human body, potentially culminating in fatality. The present study was conducted to perform forensic analysis of illicit liquors in different districts of Himachal Pradesh. In this research, 25 samples of illicit alcohol were meticulously collected from five distinct districts in Himachal Pradesh, namely Kangra, Una, Chamba, Mandi, and Bilaspur. The results of the color test revealed that ethanol might be present, but no other harmful compounds like methanol, or metals like copper and iron were detected. Furfural was found in samples S19, S22, and S23. Following that, samples were tested using an alcolyzer, which detected variations in alcohol percentage and density. Some samples had a higher alcohol percentage, indicating greater toxicity.To further corroborate these findings and identify additional constituents within illicit liquors, the samples underwent scrutiny employing Fourier-transform infrared spectroscopy (FTIR). Prospective research endeavours could expand upon this foundation by augmenting the sample size and employing advanced techniques like gas chromatography-mass spectrometry (GC-MS) for comprehensive quantitative analysis of the diverse components present in illicit liquors.

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“…However, a single word, title, or symbol poses a security threat that unscrupulous individuals will likely steal and copy. In addition, handwriting is the most common form of behavioral biometrics employed in forensic science [5]. Identifying fake handwritten documents is a challenging issue in forensic science.…”

Section: Introductionmentioning

confidence: 99%

An Enhanced Hybrid Model Based on CNN and BiLSTM for Identifying Individuals via Handwriting Analysis

Rahim,

Farid,

Miah

et al. 2024

CMES

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Handwriting is a unique and significant human feature that distinguishes them from one another. There are many researchers have endeavored to develop writing recognition systems utilizing specific signatures or symbols for person identification through verification. However, such systems are susceptible to forgery, posing security risks. In response to these challenges, we propose an innovative hybrid technique for individual identification based on independent handwriting, eliminating the reliance on specific signatures or symbols. In response to these challenges, we propose an innovative hybrid technique for individual identification based on independent handwriting, eliminating the reliance on specific signatures or symbols. Our innovative method is intricately designed, encompassing five distinct phases: data collection, preprocessing, feature extraction, significant feature selection, and classification. One key advancement lies in the creation of a novel dataset specifically tailored for Bengali handwriting (BHW), setting the foundation for our comprehensive approach. Post-preprocessing, we embarked on an exhaustive feature extraction process, encompassing integration with kinematic, statistical, spatial, and composite features. This meticulous amalgamation resulted in a robust set of 91 features. To enhance the efficiency of our system, we employed an analysis of variance (ANOVA) F test and mutual information scores approach, meticulously selecting the most pertinent features. In the identification phase, we harnessed the power of cutting-edge deep learning models, notably the Convolutional Neural Network (CNN) and Bidirectional Long Short-Term Memory (BiLSTM). These models underwent rigorous training and testing to accurately discern individuals based on their handwriting characteristics. Moreover, our methodology introduces a groundbreaking hybrid model that synergizes CNN and BiLSTM, capitalizing on fine motor features for enhanced individual classifications. Crucially, our experimental results underscore the superiority of our approach. The CNN, BiLSTM, and hybrid models exhibited superior performance in individual classification when compared to prevailing stateof-the-art techniques. This validates our method's efficacy and underscores its potential to outperform existing 1690 CMES, 2024, vol.140, no.2 technologies, marking a significant stride forward in the realm of individual identification through handwriting analysis.

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Artificial Intelligence: An Advanced Evolution In Forensic and Criminal Investigation

Cited by 5 publications

References 20 publications

Artificial Intelligence and Forensic Genetics: Current Applications and Future Perspectives

Artificial Intelligence and Forensic Genetics: Current Applications and Future Perspectives

Forensic analysis of illicit liquors in Himachal Pradesh: Assessing toxicity and composition for public health safety

An Enhanced Hybrid Model Based on CNN and BiLSTM for Identifying Individuals via Handwriting Analysis

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