Do we have to replace our cameras?

Usually no. The detection model reads your existing camera feeds and runs inference on a separate server or in the cloud, so the cameras stay in place. Most cameras installed in the last several years carry enough resolution and framerate to support it. Where a corridor is covered by an analog or very old camera, we flag that specific camera for upgrade rather than replacing the whole fleet. The free consultation tells you exactly which cameras can carry it.

Will the cameras watch residents in their rooms?

No. Coverage stays in common areas only: hallways, dining rooms, activity rooms, and corridors. There is no resident-room coverage, no audio, and no biometric identification. The system flags a posture and a location, not a named person. We map the resident-room boundary during scoping and document it, so your team and your residents' families know exactly what is captured and what is not.

How fast does an alert reach staff?

Seconds. When the model recognizes a fall in a monitored zone, it raises an alert with the clip attached and routes it to wherever your staff already looks: the nurse-station monitor, a mobile alert, or your existing call-light or paging system. The point is to close the gap between the fall and the response, especially in the overnight and shift-change windows rounds cannot cover.

What about false alarms?

Alarm fatigue is the real risk with fall detection, so tuning is most of the work. The model is calibrated per corridor, per shift, and per lighting condition, and it distinguishes a resident sitting, kneeling, or bending from a genuine fall. Senior-care environments need a calibration window before site-wide rollout. We run the system alongside your staff, adjust thresholds, and only hand off once false positives are low enough that the desk trusts every alert.

How long does it take to build and deploy?

It depends on building count and camera coverage, but the shape is consistent: a scoping walk, a build-and-integration phase against your camera feeds, then a calibration window where the model runs alongside staff before full handoff. A single building moves faster than a multi-building campus. The free consultation gives you a realistic timeline for your specific environment after we see the cameras.

Can this connect to our nurse-call or EHR-adjacent systems?

Alerts route into the systems your staff already uses, including nurse-station monitors, mobile devices, and existing call-light or paging infrastructure. We keep the camera and detection layer on a separate network segment from clinical systems and integrate at the alert and notification level, so the fall event reaches the right person without entangling the detection model in your clinical chart system.

Do we have to replace our cameras?

Usually no. The detection model reads your existing camera feeds and runs inference on a separate server or in the cloud, so the cameras stay in place. Most cameras installed in the last several years carry enough resolution and framerate to support it. Where a corridor is covered by an analog or very old camera, we flag that specific camera for upgrade rather than replacing the whole fleet. The free consultation tells you exactly which cameras can carry it.

Will the cameras watch residents in their rooms?

No. Coverage stays in common areas only: hallways, dining rooms, activity rooms, and corridors. There is no resident-room coverage, no audio, and no biometric identification. The system flags a posture and a location, not a named person. We map the resident-room boundary during scoping and document it, so your team and your residents' families know exactly what is captured and what is not.

How fast does an alert reach staff?

Seconds. When the model recognizes a fall in a monitored zone, it raises an alert with the clip attached and routes it to wherever your staff already looks: the nurse-station monitor, a mobile alert, or your existing call-light or paging system. The point is to close the gap between the fall and the response, especially in the overnight and shift-change windows rounds cannot cover.

What about false alarms?

Alarm fatigue is the real risk with fall detection, so tuning is most of the work. The model is calibrated per corridor, per shift, and per lighting condition, and it distinguishes a resident sitting, kneeling, or bending from a genuine fall. Senior-care environments need a calibration window before site-wide rollout. We run the system alongside your staff, adjust thresholds, and only hand off once false positives are low enough that the desk trusts every alert.

How long does it take to build and deploy?

It depends on building count and camera coverage, but the shape is consistent: a scoping walk, a build-and-integration phase against your camera feeds, then a calibration window where the model runs alongside staff before full handoff. A single building moves faster than a multi-building campus. The free consultation gives you a realistic timeline for your specific environment after we see the cameras.

Can this connect to our nurse-call or EHR-adjacent systems?

Alerts route into the systems your staff already uses, including nurse-station monitors, mobile devices, and existing call-light or paging infrastructure. We keep the camera and detection layer on a separate network segment from clinical systems and integrate at the alert and notification level, so the fall event reaches the right person without entangling the detection model in your clinical chart system.

Solution · Custom computer vision

Catch the fall when it happens, not on the next round.

Custom fall-detection computer vision for senior living and skilled nursing, built on the hallway cameras you already own. A fall surfaces to the desk in seconds. Common areas only, never inside resident rooms.

Book a consultation

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Call us855-577-0400

NDAA-compliant
Platform-agnostic
1,000+ deployments over 15 years

Fall-detection monitoring is custom computer vision that watches your common-area cameras for a resident on the floor and alerts staff in seconds, before the next round would find them. Tec-Tel builds the detection model against your specific environment, your camera angles, your hallway lighting, and the way your residents move, then runs it on the cameras you already own. It covers hallways, dining rooms, and activity areas only, never inside resident rooms, and routes alerts to the nurse station, mobile, or paging system your staff already uses.

Built per site

custom CV tuned to your floor plan, not a generic rule pack

Existing cameras

runs on the hallway cameras you already own

Seconds

a fall surfaces to the desk before the next round finds it

Common areas only

hallways, dining, activity rooms, never inside resident rooms

§01 What the system does

A camera that notices, and tells someone who can move.

A standard camera records a fall and surfaces nothing until a supervisor scrubs back through the footage. Fall-detection computer vision turns that same feed into a real-time event: a resident is down in corridor C at 3:14 AM, here is the clip, the desk knows now.

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Floor-event detection The model recognizes a person on the floor in a monitored zone and raises an alert in seconds. It separates a resident sitting or kneeling from a genuine fall, so the desk gets a real event, not a stream of noise.

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Quiet-hours coverage Most falls happen when staff is at the station, not in the hallway. The system watches the corridors continuously through the overnight and shift-change gaps your rounds cannot cover.

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Alert routing that fits your workflow A flagged event goes where your team already looks: the nurse-station monitor, a mobile alert, or an existing call-light or paging system. No new screen for staff to learn.

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Clip capture for review Each alert carries the short clip around the event. Charge nurses confirm severity at a glance, and the facility keeps a time-stamped record for incident documentation and family conversations.

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Zone-by-zone tuning Detection is calibrated per corridor, per shift, and per lighting condition. A west-facing dining room at sunset and a dim overnight hallway get different thresholds, which keeps false positives low.

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Privacy-bounded coverage Cameras stay in common areas only. No resident-room coverage, no audio, no biometric identity. The system flags a posture and a location, not a person.

§02 The problem

A fall found on the next round is found too late.

In senior living and skilled nursing, the gap between a fall and the response is the whole problem. A resident goes down in a hallway at 3 AM. Staff is at the station. The fall is discovered on the next round, maybe forty minutes later. By then a treatable incident has become an ambulance, a hospital transfer, and a difficult call to a family.

The cameras are already in those hallways. They record everything and surface nothing. Footage only helps after a supervisor scrubs back through it, so it documents the fall instead of catching it. The operational need is not more recording. It is the camera noticing in the moment and telling someone who can move.

Off-the-shelf video management systems were built to store and search video, not to understand a senior-care hallway at shift change. That is the gap a purpose-built solution closes.

§03 How it works

Custom computer vision, running on cameras you already have.

Fall detection is a computer-vision build, not a stock feature you toggle on. Tec-Tel develops the detection model against your environment: your camera angles, your hallway lighting, the way your residents actually move. The model reads the existing camera feeds, runs inference on a server or in the cloud, and never touches the cameras themselves.

When the model sees a person reach a floor posture in a monitored zone and hold it past a tuned threshold, it raises an alert with the clip attached. The event lands where your staff already works. Nothing about the rounds, the charting, or the call-light system has to change for the alert to be useful on day one.

Most cameras installed in the last several years carry enough resolution and framerate to support this with no hardware change. Where a corridor is covered by an analog or very old camera, we flag that camera for upgrade rather than replacing the whole fleet.

§04 When off-the-shelf fits, and when it does not

We build custom only when the stock system cannot do the job.

Plenty of operational needs are solved by a configured VMS or an established analytics platform, and when one fits, that is what Tec-Tel deploys. There is no house product to push. A custom build is the right answer only when the off-the-shelf stack genuinely cannot solve the problem in your environment.

Fall detection in senior care is often that case. Generic person-on-floor analytics built for warehouses and retail floors misread a senior-living hallway: a resident bending to a walker, a folded wheelchair, the low light of an overnight corridor. The result is alarm fatigue, and a system staff learns to ignore is worse than none. A model tuned to your floor makes the alerts trustworthy enough to act on.

→ Scope. We walk the buildings, map every monitored corridor and common area, confirm the resident-room boundary, and document camera coverage, angles, and gaps before anything is quoted.
→ Build. We develop and train the detection model against your camera feeds and environment, then connect alerts to the nurse station, mobile, or paging system your team already uses.
→ Tune. Senior-care detection needs a calibration window. We run the model alongside your staff, adjust thresholds per zone and per shift, and hand off only once false positives are low enough that the desk trusts every alert.

Questions buyers ask us

FAQ

How is this different from the analytics already built into our cameras or VMS?: Most built-in analytics are generic rule packs: line crossing, motion zones, basic person-on-floor detection trained on warehouse and retail environments. They misread a senior-living hallway and generate enough false alerts that staff tunes them out. Tec-Tel builds the detection model against your specific environment, your camera angles, your lighting, the way your residents move, which is what makes the alerts reliable enough to act on. When a stock feature genuinely solves the need, we use it. Fall detection in senior care usually is not one of those cases.
Do we have to replace our cameras?: Usually no. The detection model reads your existing camera feeds and runs inference on a separate server or in the cloud, so the cameras stay in place. Most cameras installed in the last several years carry enough resolution and framerate to support it. Where a corridor is covered by an analog or very old camera, we flag that specific camera for upgrade rather than replacing the whole fleet. The free consultation tells you exactly which cameras can carry it.
Will the cameras watch residents in their rooms?: No. Coverage stays in common areas only: hallways, dining rooms, activity rooms, and corridors. There is no resident-room coverage, no audio, and no biometric identification. The system flags a posture and a location, not a named person. We map the resident-room boundary during scoping and document it, so your team and your residents' families know exactly what is captured and what is not.
How fast does an alert reach staff?: Seconds. When the model recognizes a fall in a monitored zone, it raises an alert with the clip attached and routes it to wherever your staff already looks: the nurse-station monitor, a mobile alert, or your existing call-light or paging system. The point is to close the gap between the fall and the response, especially in the overnight and shift-change windows rounds cannot cover.
What about false alarms?: Alarm fatigue is the real risk with fall detection, so tuning is most of the work. The model is calibrated per corridor, per shift, and per lighting condition, and it distinguishes a resident sitting, kneeling, or bending from a genuine fall. Senior-care environments need a calibration window before site-wide rollout. We run the system alongside your staff, adjust thresholds, and only hand off once false positives are low enough that the desk trusts every alert.
How long does it take to build and deploy?: It depends on building count and camera coverage, but the shape is consistent: a scoping walk, a build-and-integration phase against your camera feeds, then a calibration window where the model runs alongside staff before full handoff. A single building moves faster than a multi-building campus. The free consultation gives you a realistic timeline for your specific environment after we see the cameras.
Can this connect to our nurse-call or EHR-adjacent systems?: Alerts route into the systems your staff already uses, including nurse-station monitors, mobile devices, and existing call-light or paging infrastructure. We keep the camera and detection layer on a separate network segment from clinical systems and integrate at the alert and notification level, so the fall event reaches the right person without entangling the detection model in your clinical chart system.

Book a walkthrough

Want a read on whether your cameras can carry fall detection?

The free consultation walks your buildings, maps which corridors and cameras can support detection, confirms the resident-room boundary, and gives you a realistic scope and timeline.

Tell us how many sites you run and what's already in place. We'll show you what a build or upgrade looks like.
Straight answers from the team that does the work. We're platform-agnostic, so you get the system that fits your sites, not one brand's catalog.

Since 2010 · 1,000+ deployments nationwide · ISN-accredited

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Related from Tec-Tel

Hub

Catch the fall when it happens, not on the next round.

A camera that notices, and tells someone who can move.

A fall found on the next round is found too late.

Custom computer vision, running on cameras you already have.

We build custom only when the stock system cannot do the job.

FAQ

Want a read on whether your cameras can carry fall detection?

How can we help?

AI & analytics hub

Senior living security

Healthcare security

Vision Intelligence

Operational safety

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