Vulnerable People
Acoustic monitoring for camera-restricted environments
Hospitals, rehabilitation centres and secure facilities contain environments where maintaining safety must be balanced with privacy and dignity. Acoustic AI provides an additional layer of awareness — detecting configured sound events and alerting staff when attention may be required.
A patient has a medical emergency but can’t activate their alarm. A resident in crisis calls out but the staff can’t hear. An altercation in a cell escalates before staff are made aware.
24/7 Monitoring
Real-Time Alerting
Edge AI
Privacy by Design
The Monitoring Gap
Privacy, dignity and safeguarding requirements can limit the use of visual surveillance in some of the environments where vulnerable people may require the greatest level of support.
This can create an operational blind spot. Staff cannot be everywhere at once, and conventional alarm systems often depend on an individual being able to activate them.
Acoustic AI provides an additional layer of awareness by continuously analysing the acoustic environment for configured event types and alerting staff when an event may require attention.
The objective is not to replace staff, existing alarm systems or safeguarding procedures. It is to help those systems respond to events they might otherwise not become aware of immediately.
The Acoustic AI Solution
We monitor, analyse and alert so your team can respond.
Our solution deploys acoustic sensors in the specific areas of your facility where visual surveillance is prohibited - individual rooms, bathroom facilities, consultation areas, and cells. Deeply AI's edge-based classification platform analyses sound patterns in real time, detecting the acoustic signatures of distress, aggression, and physical incidents the moment they occur.
When an event is detected, your operations or security team receives an instant alert with event type and location, enabling immediate, targeted response.
The system is designed around edge processing and data minimisation. Acoustic analysis takes place locally, with the objective of identifying relevant event types rather than identifying individuals by voice.
Deployment configuration, data handling, retention and access requirements are established for each environment as part of implementation.
Data Minimisation
The architecture is designed to minimise the acoustic data processed and retained. Deployment-specific data handling and retention requirements are agreed as part of implementation.
No Voice Identification
The system is designed to classify acoustic events rather than identify individuals by their voice.
Edge Processing
Acoustic analysis takes place locally at the edge, reducing reliance on external cloud processing and limiting the movement of raw acoustic data.
3 environments, one proven solution.
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Acoustic monitoring for single rooms, mental health wards, and any area where patient dignity or legal constraints prohibit visual surveillance.
Detect configured acoustic events associated with distress, falls or raised voices and alert appropriate staff so that the event can be investigated promptly. Event information can also support operational review and incident documentation.
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Continuous acoustic monitoring can provide an additional layer of awareness across residential environments without relying on visual surveillance.
Configured events can trigger real-time alerts, while event information can support operational review and safeguarding processes.
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Acoustic monitoring can extend situational awareness into cells, segregation units and other areas where conventional monitoring may be restricted or insufficient.
Configured acoustic events can trigger alerts for staff investigation, while event logs can support subsequent operational and incident review.
Auditable event logs for incident investigation and reporting.
What We Detect
Recognised Sound Events
Our AI analysis tool is trained on real-world acoustic data across a wide range of human distress and incident sounds.
The system differentiates between genuine emergency events and ambient background noise — delivering accurate alerts without the false positives that undermine trust in monitoring systems.
The system can be configured to monitor specific sound types relevant to your environment — sensitivity levels and active sound categories are adjustable per deployment.
Screaming & Shouting
Male Scream
Female Scream
Male Shouting
Female Shouting
Physical & Emotional Distress
Crying
Sobbing
Groaning
Glass Breaking
Disturbances
Verbal Distress
Distress Phrases
Male voice (raised)
Female voice (raised)
Conversation (elevated)
The Monitoring System
Operations & Management
Every deployment includes access to a web-based monitoring dashboard, giving your security or operations team a clear, manageable view of acoustic activity across all monitored zones.
Instant Alerting
Real-time notifications delivered via email, SMS, and webhooks — integrating with your existing operations systems and security infrastructure.
Event Management
Search and filter detected events by information such as time, location and event classification, providing an operational history of system activity.
Equipment Management
Monitor sensor connection and operational status remotely. Configure settings and perform remote restarts without on-site intervention.
Configuration Management
Adjust analysis cycles, sensitivity levels, and sound types per zone to meet your specific operational requirements.
Real-Time Analysis
Live acoustic analysis with instant event detection. Adjust analysis cycles, sensitivity levels, and active sound categories to match your specific operational requirements.
Statistical Reporting
Analyse detected events by day, time period, location and event type to identify patterns, recurring activity and areas that may warrant operational attention.
Privacy by Design
Designed for privacy-sensitive environments
Acoustic monitoring may be used in environments where privacy, data protection and human rights considerations are particularly important.
For that reason, the solution is designed around edge processing and data minimisation. Acoustic analysis takes place locally, and the system is designed to classify relevant sound events rather than identify individuals by voice.
The precise data processed or retained, retention periods, access controls and other privacy requirements will depend on the deployment configuration.
Acoustic AI Systems works with customers to establish the appropriate technical and organisational measures for each UK deployment and to support their own data-protection assessment.
Key principles:
Edge-based acoustic analysis
Data minimisation by design
Event classification rather than voice identification
Deployment-specific access and retention controls
UK deployment documentation and privacy support