Artificial intelligence (AI) and machine learning-based analytics applications have been used in the security market for a long time. Facial recognition, license plate recognition (LPR), tail gate detection and people counting are some of the applications. While analytics within video surveillance has long been central to security strategies, audio analytics has often been overlooked.  

Within security, the use of visual systems makes sense, as they allow teams to have a remote set of eyes in the field. However, this information is primarily reactive — not proactive or interactive.  

Sound and audio, however, is proactive and interactive, yet is often underutilized. Audio analytics provides critical information that cameras and other visual technologies may miss.  

Audio Analytics Explained  

At its core, audio analytics involves using machine learning to process audio input, identify patterns and trigger automated responses based on specific sound signatures. Rather than relying on human intervention to interpret sound, audio analytics systems can autonomously detect, classify and alert security teams to relevant sounds, often before an incident escalates. 

For example, audio analytics can detect aggressive tones in voices, recognize the sound of a vehicle collision, or pick up on environmental changes like fire alarms. It can also provide early warnings when conditions deviate from the norm, offering real-time insights that drive faster and more accurate decision-making. 

Unlike video analytics, which is limited to the camera’s field of vision, audio analytics can detect sounds from all directions, even in blind spots or areas with low visibility (e.g., behind walls, in the dark, or in obstructed environments). This helps security system owners to expand the detection range.  

When integrated with video surveillance, audio analytics can provide an additional context to visual footage, and therefore increasing both accuracy and reliability of video surveillance-based analytics. For example, if glass breaking is detected, audio analytics can trigger an event trigger in the VMS, prompting nearby cameras to automatically zoom in on the area, giving security teams a clear view of the situation. This multi-layered approach enhances situational awareness and delivers maximum effectiveness. 

Hear What You Can’t See 

In areas where video is not appropriate or not allowed for surveillance, sound detection using microphones from IP speakers or an IP intercom can deliver valuable information.  

  • In many parts of the world, video cameras are not legally allowed in areas such as bathrooms or showers for privacy reasons. However, in a prison, there is a daily challenge to maintain security from incidents such as alterations among prisoners, escapes and other criminal activities. Audio, however, is allowed inside the prison cells in many parts of the world, and there it can be used to detect illegal activities within legal boundaries. 
  • Audio is well positioned to detect non-visual sound-based emergencies, either due to the source is out of camera’s view or the event happens too quickly for video analysis to react. Incidents like explosions, gunshots, or screaming can be detected better. 
  • In densely packed spaces like public gatherings or concerts, video analytics may struggle to differentiate individual activities, while audio analytics can isolate specific sounds, like shouting or distress calls, even amid crowd noise. 
  • As cities grow and new infrastructures are built, the level of noise pollution poses a serious threat to public health, both physically and psychologically. This is why city officials prioritize noise reduction to improve city livability. Combining sound level detection with analytics makes it possible to analyze the level and the source of the problem, giving officials a chance to act proactively.  

Audio analytics is about detecting, analyzing and understanding audio signals captured by digital devices such as a microphone. Applications that are using audio analytics can be categorized into two key areas: 

Audio for daily operational applications — Audio Analytics can be used to improve the customer experience for daily operations such as speech recognition, translation services, automatic voice assistant and more. For example, in retail environments, audio analytics can monitor conversations, background music and customer sounds to enhance experiences, adjust service, or gauge customer satisfaction. 

Using natural language processing (NLP) as a core technology, audio analytics algorithms can contextualize speeches that are picked up by microphones from devices like IP intercoms or IP speakers.    

Audio analytics for security and surveillance — With security and surveillance, audio analytics can be a powerful tool to complement video monitoring systems. Audio analytics can detect critical sounds or threats, even outside a camera's range.  Within security and surveillance, audio analytics can:  

  • Enhance situational awareness in real time

While cameras capture visuals, audio analytics can identify important audio cues that signal potential threats or emergencies. This dual-layer approach ensures that incidents that may not be visible on camera, such as verbal altercations or subtle changes in ambient noise, do not go unnoticed. 

For example, in high-noise environments like factories, construction sites, or busy transportation hubs, audio analytics can filter out background noise to detect important sounds such as alarms, verbal distress calls, or equipment malfunctions. The system can then trigger automated alerts, providing immediate awareness and enabling a faster response. 

  • Proactive threat detection and incident prevention

In many cases, audio analytics serves as an early-warning system, detecting potential issues before they escalate into full-blown incidents. These triggers can be automatically cross-referenced with other security systems, such as video surveillance or access control, providing a comprehensive view of the situation.

For instance, in a retail setting, audio analytics can detect raised voices that may indicate a verbal confrontation between customers or employees. The system can instantly notify security personnel, allowing them to intervene before the situation intensifies. Similarly, in a healthcare facility, audio analytics can identify distressed calls or unusual noise levels in patient areas, prompting immediate action to ensure safety and care. 

  • Enhance emergency coordination and response 

During emergencies, clear communication and quick coordination are critical to minimizing risk and ensuring safety. In situations like active shooter incidents, fire alarms, or large-scale evacuations, audio analytics can pinpoint the location and type of sound, allowing teams to respond with precision and agility. 

Moreover, by integrating audio analytics with public address systems, the system can facilitate automatic messaging and instructions to guide occupants during evacuations, fire drills, or lockdowns. This creates a more efficient and coordinated response, helping to ensure the safety of individuals.