Madrid, November 28^th 2024. ISID, a technology company focused on AI platforms for video and audio, with specific solutions for the Security market, will be an exhibitor at three ISS World tradeshows, which are the world’s largest gathering of Regional Law Enforcement, Intelligence and Homeland Security Analysts, Telecoms as well as Financial Crime Investigators responsible for Cyber Crime Investigation, Electronic Surveillance and Intelligence Gathering.

ISID at ISS 2025

Every year, ISS World Programs presents the methodologies and tools for Law Enforcement, Public Safety, Government and Private Sector Intelligence Communities in the fight against drug trafficking, cyber money laundering, human trafficking, terrorism and other criminal activities conducted over today’s telecommunications network, the Internet and Social Media. ISS celebrates 5 events every year in Panama City, Washington DC, Prague, Dubai and Singapore. ISID will attend as exhibitor at the Dubai, Prague and Panama events during 2025, in February, June and October, presenting its latest enhancements and new functionalities of its Intelion platform. 

Intelion

The Intelion platform is a Video and Audio analyzer for law enforcement, government & intelligence agencies, that reduces investigation and analysis times to a fraction of the usual, by automating the tasks of reviewing and documenting video, audio, and images generated in surveillance, recordings or social media analysis operations, due the AI algorithms integrated into one single platform.

Intelion is an AI Analytics Platform that can either integrate with any VMS or work as standalone, and processes video files, or streams like live surveillance cameras, massively, in an unattended manner. It applies advanced, AI-based analyzers to automatically classify all that information and locate targets, faces, objects and any other information.

• Safe City. Intelion Safe City can connect to any VMS and enhance the security infrastructure for a Smart City or Safe City initiative. Intelion adds AI analytics layers to the VMS.
• Media Investigation. Designed specifically to facilitate police and intelligence investigations, Intelion Media Investigation is the solution that allows the massive ingestion of multimedia files or audio & video signals generated in surveillance operations (i.e. from cameras) and automates the analysis, documentation and review tasks of the videos.
• Digital Evidence Management System. Intelion Digital Evidence Management provides a complete environment where to collect, store, analyze and share digital evidence for Law Enforcement Agencies and keep the chain of custody.
• OSINT. Intelion is also able to monitor and analyze live TV and Radio, Newspapers, Documents, and gather information from social networks, and retrieve the content and the sentiment around specific topics.

About ISID

ISID is a spanish and global company that develops solutions and platforms for the processing, analysis, management and storage of audio and video. Our solutions integrate advanced AI analysis modules (like biometrics, S2T, translation, object recognition, audio fingerprinting & ID, etc.) and are used in multiple sectors, such as Security, Government and Public Administration, Law Enforcement, Intelligence, Communication Agencies, Education, Healthcare and Legal. They are AI vendor agnostic and can be integrated within the processes of the client organization and workflows.

The Role of Safe City Technologies in Modern Policing

Initially, urban surveillance relied on basic CCTV setups, which required constant human monitoring. However, Safe City technologies now includes AI-enhanced capabilities, high-definition video feeds, and seamless integration across city infrastructure, allowing police to gather real-time intelligence and respond efficiently. AI-driven systems like Intelion have brought transformative improvements to police work, enabling rapid identification of threats and streamlined investigative processes.

Key Advancements in Safe City Technologies

1. Real-time Incident Detection Safe City systems enable police to set up detection rules based on specific criteria—whether it’s monitoring for individuals of interest, identifying high-risk locations, or tracking suspicious activities. Intelion’s incident detection capabilities allow law enforcement to customize alerts, receiving notifications immediately when particular elements are detected in camera feeds, such as specific persons or behaviors. This real-time detection empowers police to proactively prevent incidents, respond faster to threats, and make data-driven decisions on the ground.

2. Tracking and Retrospective Video Analysis One of the most valuable tools for police in Safe City systems is the ability to track people and vehicles across multiple cameras, both in real time and retrospectively. Intelion provides robust tracking that lets officers reconstruct routes across the city to piece together movements of suspects or vehicles involved in criminal activities. Whether pursuing a lead from minutes ago or days prior, this tool simplifies investigations and allows police to backtrack through camera feeds, reconstructing paths and pinpointing origins.

3. Behavioral Analysis for Threat Detection Beyond simple monitoring, Safe City technology includes behavioral analysis capabilities that help law enforcement detect unusual or potentially dangerous behaviors. Intelion’s system can identify specific actions like sudden gatherings, physical altercations, or even individuals acting erratically, which could indicate intoxication, medical emergencies, or other safety risks. Police can respond to these alerts in real-time, addressing incidents that might otherwise go unnoticed until they escalate.

4. Facial Recognition for Identification In high-stakes situations where identifying suspects or missing persons quickly is paramount, facial recognition technology provides an invaluable asset. Intelion’s facial recognition capability enables law enforcement to match faces captured on video with known profiles in a secure database, providing instant confirmation. This significantly accelerates investigations, allowing police to identify persons of interest and verify identities in real-time, especially in situations where every second counts.

5. Advanced Object Recognition Object recognition in Safe City technology assists police in identifying crucial details within a scene, such as detecting weapons, identifying unusual objects left behind, or even differentiating between types of vehicles in real-time. Intelion’s object recognition feature gives police insights into elements of a scene that may be linked to a security incident, providing them with actionable intelligence and reducing response times. This helps security teams swiftly analyze situations, increasing both the accuracy and speed of police response.

6. Speech-to-Text for Enhanced Intelligence Gathering In multilingual cities or during critical events where recorded conversations hold vital clues, converting spoken language to text helps streamline investigations. Intelion’s speech-to-text capability allows law enforcement to transcribe audio from video footage instantly, aiding in searches, cross-referencing keywords, and providing translatable data for real-time comprehension of multilingual conversations. This improves evidence collection and helps police compile and analyze reports swiftly.

Benefits of Safe City Technologies for Law Enforcement

Integrating Safe City technologies into urban security infrastructure provides several tangible advantages for police and city security forces:

• Increased Situational Awareness: With AI handling numerous camera feeds, police and security personnel gain comprehensive, real-time visibility into urban areas, enabling them to prioritize high-risk zones or ongoing incidents more effectively.
• Data-Driven Crime Prevention: By utilizing advanced analytics and incident detection, police can proactively identify threats and anticipate incidents, which helps to reduce crime rates over time.
• Resource Optimization: Automated systems allow police to focus on immediate concerns rather than manually monitoring footage, freeing up personnel for other critical responsibilities and maximizing resource allocation.
• Enhanced Crime Solving and Investigation Capabilities: Retrospective analysis tools and tracking capabilities significantly aid investigative work, allowing police to reconstruct events after they occur and strengthen case evidence, particularly when tracking repeat offenders or linked incidents.

AI to the rescue

Up until recently, to know if a certain handwriting corresponded to another sample and thus the same person must have written it, a trained expert was needed: a graphologist. This requires years of specialized training to be able to function in a court and to use the findings as evidence. So up until now the graphologists were only humans, doing advanced recognition work and using years of experience in their favour.

But artificial intelligence has caught up and is not only able to read printed text with predictable fonts, but also handwritten material. In fact, it has gotten so good at it, that now this technology is used for forensic analysis. This is, to compare if a certain handwriting was written by the same person than another piece of text. These systems are collectively called FISH (Forensic Information System for Handwriting) and their main goal is to analyse all the strokes, their direction, force, pressure, etc. of a text, and then compare it to another one. The main difficulty resides in that both text are usually not the same, so a simple optical comparison could be done. Hence the need for a graphologist or, now, a FISH AI.

Why use AI to compare handwritten text?

For one, using a machine can be quicker, than sending the text out to a graphologist and waiting for the results. In some police cases or investigation, time is of the essence. But the main reason is that FISH is not only a handwriting recognition system, but a database that stores all the parameters that have been analyzed in a certain text.

This way, given a new text (for example, a threatening correspondence), the examiner can scan the document into the system, and compare it with hundreds or thousands of previously stored documents, in order to find any possible matches. For a trained human it may be easy to see if two pieces of text were written by the same person, but they cannot possibly know who wrote that particular text. A FISH system can, if there is a previous sample already stored in the database. If a match is found, that information is very useful for the investigator, as it can point him or her to a specific person. And the FISH system can find matches between thousands of specimens in a matter of seconds or minutes.

GPEC Digital 2025

Every year, the General Police Equipment Exhibition & Conference takes place at the Congress Zenter in Leipzig, Germany. They alternate between the standard GPEC, which features mainly hardware police equipment, like cars, tanks, guns, personal protection, etc. and GPEC Digital, centered on software and services for Law Enforcement. This spring ISID was an exhibitor at GPEC 2024, and next year we are going to be one at GPEC Digital 2025, presenting the latest enhancements of our Intelion AI Video, Audio & Image analytics Platform for Law Enforcement.

Intelion

The Intelion AI Video and Audio Analytics platform is in its second generation and has three variations, each one specifically tailored for its use case:

• Safe City. The Intelion Safe City variation can connect to any VMS and enhance the security infrastructure for a Smart City or Safe City initiative. Intelion adds AI analytics layers to the VMS, so hundreds or thousands of camera feeds can be monitored and searched for specific elements like faces, number plates, objects, etc. Intelion works both in real time and in retrospective.
• Media Investigation. Designed specifically to facilitate police and intelligence investigations, Intelion Media Investigation is the solution that allows the massive ingestion of multimedia files or audio & video signals generated in surveillance operations (i.e. from cameras) and automates the analysis, documentation and review tasks of the videos, reducing time and resource requirements dedicated to viewing video content or camera feeds, and providing automated analytics and alarms on detections.
• Digital Evidence Management System. Modern evidence in police cases is mostly digital nowadays. Computers, Smartphones and the Internet provide videos, photos, audio recordings, documents or social media content that can help solve a case. But the amount of data that can be collected as digital evidence is huge and requires a system that is able to manage all the information, make sense of it, analyze it, and draw conclusions from the data. Intelion Digital Evidence Management provides a complete environment where to collect, store, analyze and share digital evidence for Law Enforcement Agencies and keep the chain of custody.

About ISID

ISID is a spanish and global company that develops solutions and platforms for the processing, analysis, management and storage of audio and video, whether file-based, streaming or live (TV). Our solutions integrate advanced AI analysis modules (like biometrics, S2T, translation, object recognition, audio fingerprinting & ID, etc.) and are used in multiple sectors, such as Security, Government and Public Administration, Law Enforcement, Intelligence, Communication Agencies, Education, Media Banks, Healthcare and Legal. They are platform agnostic and can be integrated with most technology vendors and existing A/V installations.

The difference between both facial recognition systems

Facial recognition and facial recognition by similarity are related concepts, but focus on different aspects of how faces are identified and compared. The “standard” facial recognition is a broad term that refers to the technology and methods used to identify or verify a person’s identity based on their facial features. It typically involves capturing an image of a face, analyzing it using AI algorithms, and comparing it against a database of known faces. The process includes getting the facial features as precisely as posible, and creating a kind of ID fingerprint of each specific person. These IDs are compared against a database of known faces (that has been previously trained on those faces and the names assigned by hand).

Facial recognition by similarity is a more specific approach within facial recognition that emphasizes comparing the features of a given face to find similar faces, rather than strictly matching to a known identity. It focuses on using algorithms to measure how closely two faces resemble each other, and returns a “similarity score”. This means you do not get a concrete name, but how similar the current face is with one you are comparing it to. As a result, you can get clusters of similar faces or of lookalikes. The advantage of this system is that no personal information is processed, except for the original face you are comparing all others to.

General face detection technology in video

1. Usually, when processing a video looking for faces, the video stream is Split into individual frames. Each of these frames is then analyzed, looking for faces, as if it were a still photograph. In general, face detection uses Deep Learning models to find facial features in an image.
2. If a face is detected (an oval on top of a human body, usually) the system extracts its key features. These are normally the position and size of the eyes, the tip of the nose, jaw outline, lip position, ears, etc.
3. All of this information is converted into what is called a “vector” in the Deep learning lingo. This is a numerical representation of that particular face.
4. All of these vectors are matched with an existing database of face vectors. If a match is found, the person in both images must be the same. Only exact or almost exact matches are allowed.

The Early Days: CCTV Cameras

In the mid-20th century, CCTV cameras were introduced as the first line of defense for city surveillance. These cameras provided law enforcement and security agencies with a new way to monitor public spaces. While revolutionary at the time, early CCTV systems were limited. The cameras recorded footage, but operators had to manually sift through hours of video to find specific events, a tedious and inefficient process.

Still, the introduction of CCTV represented a major shift in urban security. Cities like London and New York became early adopters, installing thousands of cameras to monitor high-risk areas. While CCTV improved crime deterrence and helped law enforcement solve cases, the technology was not without its challenges. The lack of automated analytics meant that human operators were solely responsible for interpreting data, leaving room for human error and missing crucial insights.

Digital Transformation: IP Cameras and Networked Systems

The evolution of digital technology in the late 1990s brought about the next wave of urban security improvements—IP cameras. Unlike analog systems, IP cameras could connect to the internet, allowing for remote access and real-time monitoring. This digital transformation not only improved the quality of footage but also made it easier to store and share data across multiple systems.

By the 2000s, many cities had moved toward networked systems, enabling better coordination between agencies and more streamlined management of surveillance data. These systems marked the beginning of more intelligent security setups, as they allowed for greater scalability and the potential for integration with other urban management systems.

The Rise of AI and Advanced Analytics

With the emergence of Artificial Intelligence (AI) and advanced video analytics, city surveillance underwent another revolutionary shift. No longer were security systems limited to mere video recording; they now had the capacity to analyze footage in real-time. AI-powered analytics could detect unusual behavior, track individuals across multiple cameras, and even recognize faces or license plates.

These capabilities transformed urban surveillance into proactive systems. Instead of waiting for crimes or incidents to happen, AI analytics could alert authorities to potential risks before they escalated. Machine learning models could also predict patterns in criminal activity, leading to better resource allocation and faster response times.

Smart City Technology: An Integrated Approach to Safety

As cities grow and evolve, the concept of a “smart city” has emerged as the ultimate realization of urban safety and efficiency. Smart cities integrate various systems—traffic management, public utilities, waste collection, and, of course, security—into one cohesive network. Using Internet of Things (IoT) devices, cloud computing, and AI, these cities can optimize resources, reduce costs, and, most importantly, ensure public safety.

In the realm of security, smart cities take surveillance to the next level. AI-driven safe city solutions use real-time data from millions of connected devices to provide a comprehensive view of urban environments. From monitoring public spaces and transportation hubs to detecting potential threats, smart city technology is designed to ensure the safety of all residents in the most efficient and automated manner possible.

The Key Benefits of Safe City Technology

As cities grow and evolve, so do the challenges of maintaining safety and security. Traditional methods of urban safety are increasingly being supplemented—and in some cases, replaced—by innovative technologies designed to create smarter, safer cities. Safe City Technology encompasses a range of solutions, from advanced surveillance systems to AI-driven analytics, all aimed at making urban environments more secure and livable.

Below, we explore the key benefits that these technologies offer, showcasing why they are becoming indispensable tools for modern cities:

Crime Reduction

One of the most significant benefits of Safe City Security is its ability to reduce crime. Advanced surveillance systems equipped with high-definition cameras and real-time monitoring can detect suspicious activities before they escalate into criminal acts. These technologies allow law enforcement agencies to respond swiftly, preventing crimes such as theft, vandalism, and assaults. Moreover, the presence of visible surveillance acts as a deterrent, discouraging potential offenders from engaging in illegal activities.

Improved Emergency Response

Safe City Security also enhances emergency response times. With the integration of smart sensors and communication networks, authorities can quickly identify and address emergencies such as fires, accidents, or medical incidents. This rapid response capability saves lives and minimizes the damage caused by such events. Additionally, the use of predictive analytics can help in anticipating and preventing potential threats, making cities more resilient to emergencies.

Enhanced Public Safety

Beyond crime reduction, Safe City Technology contributes to overall public safety by monitoring and managing various urban activities. For example, intelligent traffic management systems can reduce the likelihood of accidents by controlling traffic flow and detecting hazardous conditions on the roads. Similarly, environmental monitoring systems can detect air and water pollution levels, ensuring that the public is alerted to potential health risks.

Better Quality of Life

As cities become safer, the quality of life for residents improves. A secure environment encourages economic growth, attracting businesses and tourists, and boosting the local economy. Moreover, citizens feel more comfortable engaging in outdoor activities, attending events, and using public transportation, knowing that their safety is being actively monitored and protected.

Cost-Effective Security Solutions

Implementing Smart Safety Solutions can lead to cost savings in the long run. Automated systems reduce the need for a large workforce to monitor security feeds, as AI-driven analytics can identify and flag potential issues. This efficiency not only lowers operational costs but also allows law enforcement to allocate resources more effectively, focusing on critical areas that require human intervention.