AI in Private Investigations: The Impact of Artificial Intelligence

 

The rapid evolution of artificial intelligence (AI) has had a profound impact on a wide array of industries, transforming how businesses operate and deliver value to their customers, but how will AI in private investigations change modern investigative techniques? The private investigation industry, traditionally reliant on human intuition, observation, and manual data analysis, is no exception to this trend. As AI continues to develop, it promises to revolutionise how private investigators conduct their work, offering tools that can increase efficiency, accuracy, and depth of analysis. This blog post explores the potential of AI in private investigations, how similar technology is already in use, and predictions for the future of the industry.

How ArtificiaI Intelligence Has Affected Other Industries

AI has already reshaped numerous industries, enhancing productivity and enabling tasks that were previously unimaginable. In healthcare, AI-driven diagnostic tools can analyse medical images with remarkable accuracy, often surpassing human experts. Financial services utilise AI to detect fraudulent activities in real-time by analysing transaction patterns. In the retail sector, AI powers recommendation engines that personalise shopping experiences based on customer behaviour.

 

These advancements have been made possible by the ability of AI to process vast amounts of data quickly, identify patterns, and learn from them. The implications for private investigators are significant, as the industry also relies heavily on data collection, pattern recognition, and decision-making based on incomplete or complex information.

How Will We See AI In Private Investigations? Here’s Our Predictions

As AI technology continues to evolve, several key areas in private investigation are likely to see significant transformation. Here’s a closer look at some predictions:

Smart Motion Detection Alerts with Camera Equipment

AI-powered covert camera systems can enhance surveillance by providing smart motion detection alerts. These systems can distinguish between different types of motion (e.g., human, animal, or vehicle) and filter out false positives, which reduces the workload on investigators and makes them a practical solution for longer deployments when live viewing isn’t feasible. However, this technology is not brand new and is available across a wide range of equipment available on the market today.

A key benefit is that it enables private investigators to monitor locations more effectively, minimising the need for constant human oversight. AI systems can alert investigators to suspicious activity in real-time, allowing them to monitor multiple areas and with greater accuracy. With the improvement in Artificial Intelligence we believe that alerts will be further customisable, allowing specific criteria such as vehicle registration plates and specific faces or characteristics to be implemented into the filter. For example; A covert camera could be deployed at the entrance to a communal car park and only send a notification if the subject’s vehicle was detected rather than any vehicle.

Predicted Routes from Vehicle Tracking Devices

Vehicle tracking devices equipped with AI can analyse historical data and current movement patterns to highlight individual journeys a vehicle has taken and point out basic data such as frequent locations, or the duration a vehicle has spent at a given location. We would like to see Artificial Intelligence implemented in a way that would allow predictions about the drivers route to be delivered to the investigators in real-time. These predictions can be crucial in planning surveillance operations, especially when trying to anticipate the movements of a subject who may be aware of being followed.

For example, if a tracking device had been gathering data for 14 days and it had identified there were three known routes between the work and home address. An investigator could enable predictive mode within the tracking app which could then highlight upcoming turns or likely routes which allow the surveillance team to take alternative routes and reduce exposure by following from greater distances.

In instances where the vehicle was being followed, the tracking app could show a predicted destination area, for example, if a vehicle travelling North on the M6 travelled past Junction 5, it would be unlikely that the vehicle was heading to a destination within central Birmingham. This is mildly useful in the context of a motorway but when a vehicle travels into more remote or rual areas, it would be quite apparent that after a certain combination of turns, there was only a relatively likely destination area, the futher into the journey the vehicle travelled, the more precise the device could predict the destination.

 

This information would be apparent to a local private investigator who knew the minor roads and the area, but surveillance can be unpredictable and surveillance operators often end up travelling to remote or unknown locations whilst following a subject.

Reconnaissance Visits Conducted by A.I Powered Technology

Private Investigators can be deployed to conduct reconnaissance of locations, but budget doesn’t always permit it (more often than we would like!) and many recce’s are conducted on Google Earth where the images are often months, or years out of date. Ultimately reconnaissance visits are an essential part of planning surveillance operations. Any risks, hurdles or concerns that can be identified during the recce, provide the investigator with more time to mitigate them before the investigation goes live.

 

Whilst drones can be used to gather ariel footage, it requires an investigator to travel within a couple of Km of the location to manually record the plot and its surrounding areas. Investigators map out areas, identify potential entry and exit points, lay-up positions and even security measures such as cameras or access restrictions. It also gives them an opportunity to identify vehicles of interest and this is crucial when a direct view of the property is not possible.

 

Using artificial intelligence a drone could produce an ariel map of the property, surrounding areas, and also identify objects such as vehicles. By inputting a point of interest and basic requirements the drone could travel a methodical route covering the property and surrounding area then stitch the imagery together to create a virtual, 3D image of the plot which can provide more up to date location data to the investigator. A.I reconnaissance could save time and reduce the risks associated with manual scouting but it would still require the investigator to travel to the location.

It is unlikely that we will see the implementation of cellular data in drones due to airspace restrictions and privacy laws that require them to be within a certain proximity of the controller. The implementation of cellular data could allow them to be controlled via regular cell networks over much larger distances however this would also require significant improvements in battery life.

 

 

Image Recognition from Open-Source and Social Media Intelligence

AI-based image recognition can be a powerful tool in social media intelligence (SOCMINT). These systems can scan millions of images across social media platforms to identify a person of interest and uncover connections between individuals. Image recognition can be fantastic for identifying false profiles and locating the original sources however there are limits to what it can detect.

The ability to analyse vast amounts of visual data quickly and accurately will allow private investigators to uncover leads that would have been missed through manual analysis. This capability will improve as search tools allow increasingly specific criteria such as location data and registration plates within images.

Examples of Similar Technology Already in Use

While the full integration of A.I in private investigations is still on the horizon, several technologies that utilise AI principles are already in use, laying the groundwork for more advanced applications.

Facial Recognition Software

Many businsses already use facial recognition software to identify individuals in crowds or match images from social media profiles to known subjects. This technology is particularly useful in identifying persons of interest or confirming the identity of individuals who are banned from commercial premises.

Facial recognition relies on A.I algorithms to analyse facial features and match them against a database of images. This technology has proven to be highly effective, although it raises privacy concerns that must be managed carefully.

Predictive Analytics

Predictive analytics, powered by A.I, is used in fraud detection to identify patterns that suggest fraudulent behavior. For financial institutions, this technology can help flag suspicious financial transactions or behaviors that warrant further investigation.

A.I systems can analyse large datasets to identify anomalies or patterns that humans might overlook. This technology is already used in financial institutions and is increasingly being adopted by private investigators for fraud and financial investigations.

AI-Driven Motion Tracking with Pan-Tilt-Zoom (PTZ) Cameras

Pan-Tilt-Zoom (PTZ) cameras equipped with AI-driven motion tracking are used in various commercial settings (and even some home CCTV cameras offer the funcitonality now). These cameras can automatically follow a moving subject by adjusting their pan, tilt, and zoom functions in real-time, ensuring that the subject remains in focus and within the frame.

The AI in these systems enhances the camera’s ability to differentiate between types of motion (e.g., human, animal, or vehicle) and follow the most relevant activity without human intervention. The AI algorithms process real-time video feeds, allowing the camera to predict the movement of subjects and adjust its position accordingly. This technology is particularly useful in scenarios where continuous manual operation of the camera is impractical.

Conclusion

The integration of A.I in private investigations has the potential to transform the industry, offering tools that can enhance efficiency, accuracy, and overall effectiveness. As AI continues to evolve, private investigators who embrace these technologies will be better equipped to handle complex cases, uncover critical evidence, and provide their clients with the best possible outcomes.

However, as with any technological advancement, there are challenges to consider, including the ethical implications of AI in surveillance and the need to balance technological capabilities with privacy rights. As AI becomes more prevalent in private investigations, it will be crucial for the industry to develop standards and best practices that ensure these tools are used responsibly and effectively.

The future of private investigations is undoubtedly intertwined with the advancement of AI, and those who stay ahead of the curve will find themselves at the forefront of this evolving field. Whether it’s through smart motion detection, predictive analytics, or AI-powered reconnaissance, the next generation of private investigators will have an arsenal of cutting-edge tools at their disposal, making the industry more dynamic and capable than ever before.

Written By David Jones of Reveal Private Investigators Birmingham