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By:

Dr. Abhilash Dawre

19 March 2025 at 5:18:41 pm

Eleven killed in van accident

Thane: In a tragic accident that claimed 11 lives within moments, a passenger van collided head-on with a cement mixer on the Kalyan–Ahilyanagar National Highway near Rayate village in Kalyan taluka, leaving the entire Thane district shaken. The impact was so severe that all passengers in the van died on the spot, turning multiple families’ lives upside down.   The accident took place on a bridge over the Ulhas River. The van was completely crushed, reduced to a mangled heap of metal. Despite...

Eleven killed in van accident

Thane: In a tragic accident that claimed 11 lives within moments, a passenger van collided head-on with a cement mixer on the Kalyan–Ahilyanagar National Highway near Rayate village in Kalyan taluka, leaving the entire Thane district shaken. The impact was so severe that all passengers in the van died on the spot, turning multiple families’ lives upside down.   The accident took place on a bridge over the Ulhas River. The van was completely crushed, reduced to a mangled heap of metal. Despite immediate rescue attempts by local villagers, not a single life could be saved.   While speaking to, ‘The Perfect Voice’ , Thane Civil Surgeon Dr. Kailash Pawar confirmed that all 11 victims died on the spot. The bodies were subsequently shifted to the rural hospital in Goveli for post-mortem examinations. Heart-wrenching scenes were witnessed at the hospital as a large number of relatives gathered, grieving the sudden and tragic loss of their loved ones.   Out of the deceased, nine have been identified while two remain unidentified. The victims include eight men and three women. Identified individuals include  1) Prashant alias Bablu Rupesh Chandane - 21 years, Devgaon, Murbad. 2) Bhushan Ghorpade - 49 years, Andheri, Mumbai; Revenue Assistant at the Tehsildar Office, Murbad. 3) Jija Govinda Kembari - 50 years, Tembhare, Murbad. 4) Ananta Pawar - Sakhare, Murbad. 5) Deepak Gavali - Resident of Kalyan. 6) Ganpat Jainu Madhe - 32 years, Devaralwadi, Murbad. 7) Sneha Mohpe - approximately 22 years, Narayangaon, Murbad. 8) Mansi Mohpe - approximately 20 years, Narayangaon, Murbad. 9) Prathamesh Mohpe - approximately 17 years, Narayangaon, Murbad.   The tragedy has left behind grieving families, unanswered questions, and renewed concerns over road safety on this highway.   Three siblings among killed What began as a simple journey ended in unimaginable tragedy. Three siblings who had left home saying, “We’ll be back in a few days, Mom,” lost their lives in the horrific accident near Rayate bridge, leaving their mother devastated and alone. Sneha Mohpe (22), Mansi Mohpe (20), and Prathamesh Mohpe (17), residents of Diva, were among the 11 victims of the crash. The three were raised single-handedly by their mother, Anjana Mohpe, after their father passed away seven years ago. Despite financial hardships, Anjana Mohpe worked tirelessly in household jobs to educate her children and build a better future for them. The siblings were studying in Diva and Thane and had recently left for Parhe village in Murbad taluka to visit their uncle during college holidays.   However, fate had other plans. Their journey ended abruptly when the passenger van they were travelling in collided head-on with a cement mixer near Rayate bridge, killing all on board instantly.

AI at Borders: Detecting Deception in Real Time

AI-powered surveillance systems are redefining border control by detecting deception through micro-expressions, stress patterns, and speech anomalies.


In an era of increasing global mobility, ensuring the security of national borders has become a critical priority for governments worldwide. Airports and seaports serve as vital entry points, making them prime targets for illegal immigration, human trafficking, and other transnational crimes. Traditional security measures, such as document verification and background checks, are no longer sufficient to address the growing sophistication of deception techniques. As a result, behavioural deception detection technologies, including suspect detection systems, layered voice analysis, and AI-based emotion detection cameras, have emerged as key tools in identifying individuals attempting to enter countries under pretences.


Behavioural deception detection relies on analysing micro-expressions, physiological responses, and speech patterns to identify inconsistencies that may indicate dishonesty. One such technology is the Suspect Detection System (SDS), which combines biometric analysis, facial recognition, and stress-level assessment to evaluate passengers at border checkpoints. This system works by asking targeted questions and measuring involuntary physiological responses, such as eye movement, pulse rate, and skin conductivity. SDS has been successfully deployed in various countries to flag suspicious travellers before they proceed further into immigration clearance.


Another effective technology in deception detection is Layered Voice Analysis (LVA). Unlike traditional polygraph tests, which require physical sensors, LVA analyses vocal characteristics to detect emotional stress and cognitive dissonance. It evaluates variations in pitch, tone, and speech hesitation to identify potential deceptive behaviour. Used by security agencies worldwide, LVA has proven particularly effective in uncovering inconsistencies in the statements of travellers suspected of using forged documents or concealing their true intentions. Its ability to provide real-time deception assessments makes it a valuable tool in high-traffic areas such as airports and seaports.


AI-driven emotion-detection cameras further enhance border security by analysing facial expressions and body language. These cameras use deep learning algorithms to detect micro-expressions that are difficult to conceal, such as fleeting signs of anxiety or nervousness. By integrating these systems with existing security infrastructure, authorities can identify high-risk individuals with greater accuracy. Several countries, including the United States, the Netherlands, and Israel, have incorporated AI-based surveillance at major entry points to improve security screening processes.


Globally, deception detection measures have led to significant breakthroughs in security. In the Netherlands, the Schiphol Airport employs AI-driven travel surveillance to assess passenger risk based on behaviour patterns and travel history. In India, deception detection has played a crucial role in curbing illegal immigration at major international airports, such as Indira Gandhi International Airport in New Delhi. In 2024 alone, Delhi Police arrested 203 individuals involved in immigration fraud, marking a 107% increase from the previous year. These arrests were made possible through enhanced behavioural analysis techniques and advanced document verification methods.


Statistical insights further emphasise the importance of deception detection in immigration security. In 2024, Delhi Police's crackdown on fraudulent immigration agents led to a record number of arrests, with most offenders hailing from Punjab (70), Haryana (32), Delhi (25), Uttar Pradesh (25), and West Bengal (17). Such figures underscore the prevalence of immigration fraud across various regions and highlight the need for ongoing advancements in deception detection technologies.


The scope of behavioural deception detection in India is vast, with significant opportunities for enhancement. By integrating AI-powered emotion detection, real-time voice analysis, and biometric monitoring, Indian airports and ports can strengthen their security frameworks. Investing in advanced training programmes for immigration officers, fostering international collaborations, and leveraging AI-driven analytics can further bolster national security. Public awareness campaigns on the risks of immigration fraud can also act as a deterrent, ensuring a more secure and transparent border control system.


(Dr. Kumar is a retired IPS officer and forensic consultant to the Assam government. Reddy is Forensic Psychologist and Industrial & Corporate Security Professional.)

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