Two unidentified persons allegedly staged a road confrontation and robbed mobile phones and accessories worth ₹24.53 lakh, brought from abroad, at the Dahisar check naka in the early hours of the morning. The Dahisar Police have registered a case of robbery against the absconding accused and have launched a search operation with the help of CCTV footage.
The complainant, Vijay Pawar (38), is a native of Ahmedabad, Gujarat, and is currently employed with a private company in Dahisar. On December 1, the company owner, Jigar Badia, had sent Pawar along with his colleague Archana to Hong Kong for official work. During their stay in Hong Kong, they purchased mobile phones and related accessories. At Hong Kong airport, they were joined by their associate, Deepak Belladia.
All three returned to Mumbai on January 23 and landed at Chhatrapati Shivaji Maharaj International Airport. After exiting the airport, they hired a car and were travelling towards the Dahisar check naka near a CNG gas station at Prabhat Industries via the Ovari Pada Bridge.
At around 2:45 am, two youths riding a Bullet motorcycle stopped their car and alleged that the car had hit their motorcycle, asking them to pull over. As soon as the trio stepped out of the car, the two men engaged them in an argument and, taking advantage of the distraction, allegedly stole a bag containing mobile phones and accessories from the car’s boot before fleeing the spot.
The stolen articles are valued at ₹24,53,680 and include three iPhone 17 Pro handsets worth ₹2.85 lakh, two iPhone 17 Pro Max handsets worth ₹2 lakh, small memory cards worth ₹6 lakh, large memory cards worth ₹12 lakh, pen drive memory cards worth ₹36,180, iPhone mobile screens worth ₹1,30,500, along with a mobile phone belonging to Deepak Belladia.
Following the incident, Vijay Pawar approached the Dahisar Police and lodged a complaint. After verifying the complaint, the police registered a robbery case against the unidentified accused. Further investigation is underway, and police have initiated a special drive to identify and arrest the suspects using CCTV footage from the area.