Video analytics-driven solutions to enhance data collection processes.

India currently has close to 700 toll plazas spread across approximately 30,000 kilometers of highways, with plans to expand toll infrastructure by an additional 7,800 kilometers of expressways under a five-year roadmap. This expansion is driven by the rising number of vehicles and the growing demand for transportation infrastructure. However, with limited resources, governments are facing a dual challenge: addressing existing maintenance backlogs while also accommodating the infrastructure needs of a rapidly growing population. In such a scenario, it is essential for toll plazas to embrace advanced technologies that align with public expectations and optimize operational efficiency. Rather than investing heavily in new infrastructure, the focus must shift towards maximizing the performance of existing assets. Enhancing operational efficiency not only reduces costs but also improves customer satisfaction, extends asset life, and enhances overall utilization. One of the key areas for improvement is the use of video analytics and data-driven systems for tolling and traffic operations. As both public and private infrastructure stakeholders seek cost-effective solutions, innovative tolling technologies—such as Open Road Tolling (ORT), Electronic Toll Collection (ETC), and GPS-based systems—are transforming the industry. These advancements streamline operations, reduce congestion, and significantly cut travel time. To complement these efforts, the Government of India has introduced several road safety initiatives, including amendments to the Motor Vehicle Act, the implementation of the Good Samaritan Law, nationwide awareness campaigns, and substantial funding for the identification and rectification of accident-prone black spots. Video analytics can play a crucial role in supporting these initiatives. Research shows that the faster emergency responders arrive at an accident scene, the greater the chances of survival. Advanced video analytics software, when applied to live CCTV feeds, can detect violations or accidents in real time and alert traffic control centers instantly—facilitating immediate emergency response. Similar systems are already in place globally. For example, the city of Ashdod in Israel has deployed a smart traffic monitoring system to enhance road safety and reduce congestion. Countries like the United States, Singapore, the United Kingdom, Ireland, and Iraq have also adopted crash detection systems. British startup Axitech has developed automated collision detection and management systems using cloud-based algorithms for both emergency (eCall) and breakdown (bCall) situations. In the U.S., GeoZilla offers a smartphone app that detects crashes using motion sensors and sends emergency alerts with GPS coordinates. Singapore-based Tangerine provides fleet management solutions capable of crash detection through its Jido product line, which integrates sensors such as accelerometers, gyroscopes, and magnetometers to analyze vehicle behavior and pairs this with AI-powered video analytics for a comprehensive accident detection tool. In Indian cities, the need for video analytics-based solutions is more critical than ever for improving data collection, enhancing data quality, and driving informed decision-making. With rapid technological advancement, numerous private players have begun offering data-driven traffic solutions aimed at traffic monitoring and management, improving road safety for non-motorized transport (NMT) users, and enforcing traffic violations and lane discipline. SURAAN Tech Solutions provides a comprehensive Traffic Video Analytics and Automation Platform, offering a next-generation foundation for traffic monitoring and control. This all-in-one solution delivers situational awareness and actionable insights by analyzing all types of movements through camera networks of any scale. The system is capable of automatically detecting and classifying all objects, including pedestrians and cyclists, identifying congestion and incidents, analyzing traffic behavior in detail, and performing predictive analytics. It supports real-time data collection, capturing parameters such as vehicle speed, travel time, license plate recognition, road user paths, journey duration, and more. Through telematics integration, the platform can interpret vehicle movements, assess level of service, generate origin-destination (OD) matrices, produce heat maps, detect blind spots, and deliver customizable traffic insights in real time. It serves as an ideal non-intrusive monitoring tool for highways, two-lane roads, and urban traffic environments alike. In addition, the system tracks vehicle trajectories, logs the time of every traffic event, detects stopped vehicles, wrong-way driving, and illegal parking. It also monitors driver speed behavior in critical zones such as blind spots or hairpin bends—areas with high accident potential—enabling authorities to implement proactive safety measures.