Passenger counting is a crucial function in the management of public transport and relies on advanced technologies that include surveillance cameras and our Artificial Intelligence algorithms for data analysis.

It allows companies to monitor attendance in real time, adjust the frequency and capacity of vehicles to actual needs, and optimize resources. For example, during peak hours or special events, an effective counting system can help prevent overcrowding and improve the quality of service offered to users.

Historical analyses of passenger flows can indicate changes in travel patterns and prompt infrastructural changes, such as adding new lines or stops.

It also allows for the reduction of energy wastage and the optimization of routes based on actual demand, reducing the environmental impact of the sector.

The Origin-Destination matrices, created through our Artificial Intelligence algorithms, are fundamental analytical tools in the field of transport planning. These matrices collect and analyze data on the routes taken by passengers, indicating the starting and ending points for each journey within a transport network. The use of this information allows operators to better understand traffic flows, optimize existing routes, and plan new lines or services based on actual demand. The collected data are essential for modeling and predicting urban mobility behaviors and for supporting policy and operational decisions that influence urban development. For example, a detailed analysis of the matrices can reveal the need to increase public transport services in rapidly growing areas or to adjust service schedules to respond to emerging commuting patterns.

Monitoring the occupancy of seats and reserved areas is another vital aspect of public transport management, as it directly affects the quality of service offered to users and their accessibility to the transport vehicle. This function involves detecting the actual use of seats and areas designated for specific categories of passengers, such as the elderly, disabled, or pregnant women.

Images from cameras are analyzed by our Artificial Intelligence algorithms to inform passengers waiting at the stop about the availability of these areas.

Detailed analyses allow for the quick identification of any misuse of the reserved areas and interventions to optimize the use of available space, contributing to a more equitable and accessible environment for all users. Advanced management of seat occupancy and reserved areas not only improves the travel experience for each individual but also ensures that inclusivity policies are respected and that the needs of all passengers are considered fairly and responsibly.

Monitoring the number of passengers boarding and alighting from a transport vehicle is crucial for efficient management and safety in public transportation. This metric, particularly relevant for buses, trains, and other mass transit vehicles, allows operators to assess the distribution of passenger load across various stops and optimize the service accordingly. NCM uses cameras for counting boardings and alightings, which may be the same as those used for video surveillance, and Artificial Intelligence algorithms that analyze the flows of people entering and exiting at stops. These systems are capable of distinguishing even complex situations, such as groups boarding or alighting together, providing accurate data useful for making operational and planning decisions.

In the transport sector, fraud identification is a critical component for ensuring financial and operational transparency of companies. Thanks to technological advancements and the adoption of smart monitoring and analysis systems, organizations can now proactively address the risk of fraud, protecting both their assets and customer trust.

Fraud in the transport sector can take many forms, from fare evasion to the misuse of company resources, to data manipulation for personal or corporate gain. To effectively combat these risks, NCM implements a range of advanced technological solutions to identify and prevent fraud before it can have a significant impact.

Monitoring Technologies

One of the most effective tools in fighting fraud is real-time monitoring through surveillance cameras and sensors integrated into transport vehicles and infrastructure. These devices not only record suspicious activities but are also integrated with our AI software, which can analyze behaviors and identify unusual patterns. For example, an unusual increase in the number of passengers at a particular location without a corresponding increase in ticket sales could indicate a fare evasion issue.

Payment System Integration

To minimize transaction-related fraud, NCM implements integrated and secure payment systems. These systems use encryption technologies and biometric authentication, such as palm or facial recognition, to ensure that only authorized passengers can access paid services. This significantly reduces the chances of fare fraud and enhances the security of financial transactions.

In conclusion, fraud identification is a key element in maintaining the integrity and financial sustainability of the transport sector. Through the use of AI, NCM is at the forefront of combating fraud, ensuring a reliable and secure service for all its users.

NCM's advanced surveillance system integrates artificial intelligence (AI) to provide self-monitoring capabilities that ensure its constant efficiency and reliability. This innovative feature, named "Watch the Watchers," represents a qualitative leap in how security infrastructures are monitored and managed.

The ability of a surveillance system to self-check is crucial, especially in critical environments such as transport stations, airports, and logistics hubs, where security can never be compromised. Traditionally, the maintenance and control of surveillance systems required frequent and costly human interventions, with periodic checks to ensure the proper functioning of cameras and related network infrastructures. With the introduction of AI, NCM transforms this paradigm.

The "Watch the Watchers" system uses AI algorithms to continuously monitor the operational health of every camera and system component. This includes checking camera functionality, analyzing image quality, detecting any failures or signal degradations, and early identification of tampering or sabotage attempts.

One of the most innovative aspects of the system is its self-diagnostic capability. If a problem is detected, such as a obscured lens, a sudden change in recording settings, or a network connection disruption, the system not only immediately notifies operators but in many cases can also attempt automatic corrective actions. This reduces downtime and maximizes operational continuity.

Furthermore, AI allows for continuous optimization of recording configurations based on the analysis of collected data. For example, if an increase in suspicious activities is detected during certain hours in specific areas, the system can automatically adjust the recording resolution or the frame rate of the affected cameras to capture finer details and improve evidence collection.

Ultimately, with its innovative approach to the maintenance and control of surveillance systems, NCM sets new standards of safety and reliability, ensuring its customers the peace of mind that comes from knowing their environment is always protected and monitored.