Staffing a Real-Time Crime Center When Software Does the Watching

Most chiefs who hear a pitch for a real-time crime center ask the same question before any other, which is whether they will have to hire a room full of analysts to watch the screens, and for most of the history of these centers the answer was yes. That answer rested on treating the watching of cameras as the job, and software can now watch every camera at once, all the time, which no team of people can do. It will still be wrong sometimes, so a person checks an alert before anyone is sent, but the watching itself no longer needs a room full of people. What follows works out what staffing looks like after that change, building on our guide to what a real-time crime center is, and how to calculate the number your own center needs.

Why the old model needed so many people

The traditional real-time crime center was built around a video wall and a row of people watching it, and every staffing number that came out of that model followed from how little a person can watch well. Someone looking at a wall of feeds can give real attention to a handful of screens for a limited stretch, so covering more cameras meant more people, and covering more hours meant multiplying those people by shifts. A seat that has to be staffed around the clock needs 168 hours of coverage a week, which is 4.2 full-time people at a forty-hour schedule before leave, training and turnover, and close to five once those are counted.

Federal guidance written for that model reflects how many people it took to run, and an older planning guide from the Bureau of Justice Assistance put a round-the-clock center at about twelve full-time staff, and the largest centers in the country are staffed on that pattern, with New York's run by full-time investigators on three shifts, according to Police1. Most agencies looked at those numbers and concluded, reasonably, that a real-time crime center was something for other departments.

What the software takes off people's hands

Camera analytics changes the arithmetic because it takes over the work that consumed most of those seats, and the rest of the staffing plan depends on being specific about which work that is.

The software watches every camera it is connected to, continuously, for the conditions it has been told to look for, such as a person in a closed park after midnight, a vehicle stopped on a highway shoulder or someone lingering by a closed storefront. When one of those conditions occurs it raises an alert with a snapshot or clip, the camera, the time and a severity, so nobody has to be looking at the right screen at the right moment. It can also decide where each alert goes, sending it into the systems people already use, such as a dispatch workflow, a supervisor's messages or a case file, depending on the type of alert and the time of day. On some platforms an automated step can run on each alert before a person sees it, pulling related records or applying conditions a simple camera rule cannot express, so that what reaches a person is more complete. And the system records all of it, keeping the footage, the alert and who handled it, which removes a large amount of manual logging.

None of that requires anyone to sit in front of a video wall, and it means the question of how many people it takes to watch four hundred cameras no longer has to be answered.

What still needs a person, and why

What remains is judgment and accountability, and each part stays with a person for reasons that better software will not remove.

Checking an alert before an officer is sent comes first, because no detection system is right every time, and sending officers to a situation that turns out to be nothing carries real risk for the public, for the officers and for the agency. Cities have started writing this into policy, and Seattle's AI policy, updated in 2025, bars the use of AI for consequential decisions and requires that AI output be reviewed by a person, according to KNKX.

Once an alert is confirmed, someone has to decide what to do about it, whether that means asking dispatch to create a call, watching and waiting, passing it to a detective or doing nothing at all. During a live incident, someone who knows what an officer on the way needs to hear, and when to stay off the radio, has to do the talking. After the fact there is investigative follow-up, such as building a timeline or pulling footage for a case, and someone has to answer for all of those decisions later, in court, in response to a records request or in front of a council. The person in the room has become a decision-maker who is interrupted only when the system has something to decide about.

Staffing to decisions rather than cameras

Once watching is handled by software, the number that drives headcount becomes the count of decisions per shift the system hands to people, rather than the number of cameras, and the agency controls that count through the rules it sets.

Every rule produces some volume of alerts, and every alert that needs a person's judgment takes some minutes of that person's time, so the planning exercise is to estimate alerts per shift by rule and multiply by the time each one takes to check and act on. A rule watching a closed park overnight might produce a few alerts a week, while a rule on a busy intersection might produce dozens a day, and a rule that produces more alerts than anyone can read properly is a rule that needs to be narrowed or dropped rather than a reason to hire. The National Institute of Justice noted in a 2025 technology brief that there is little research on optimal staffing and recommended starting from an analysis of calls for service by hour and day, and alert volume by hour is the same kind of analysis applied to the camera side.

A simple worksheet is enough to start with, and it should be revisited every time cameras, rules or staffing change.

Adding up the minutes by hour shows where the decisions concentrate, and that is what tells you whether you need a dedicated person at all.

Event days and bad nights are the exception to the idea that the agency controls its alert volume, because a stadium crowd, a festival or a storm can push the number of alerts well past what the usual rules and people were sized for. Plan for them separately: a lighter rule set for event days that holds back low-priority alerts, extra staff or borrowed analysts scheduled in advance, and a written agreement on which alerts still go straight to dispatch while the room is overloaded.

Three staffing shapes that follow

Most agencies land in one of three shapes once they staff to decisions, and the first is where most small and mid-size agencies can stay.

Where alerts go is configurable to each city's own workflow, by alert type and by hour, so the same system can send loitering alerts to a patrol supervisor's phone, fire and smoke to dispatch and everything else to a morning review queue. In the first shape that work lands on people who already have jobs, so whoever receives the alerts takes it on, and the routing should be agreed with them in writing, and with the 911 director if any alerts go to dispatch, since many emergency communications centers are short of staff themselves, as our article on getting camera alerts to 911 dispatch explains. Agencies that want the third shape without building it can join a center someone else runs, which our guide to real-time crime centers for small agencies explains.

Who the decision-makers should be

Because the job is now judgment rather than watching, the question of who fills it shifts toward people who know how officers work and how to weigh an ambiguous situation quickly.

The NIJ brief sets out the tradeoffs between sworn, civilian and mixed staffing and concludes that a mix is likely to work best. Sworn staff bring field experience and know what an officer on the way needs to hear, but they cost more and rotate out. Civilian analysts, often recruited from dispatch or crime analysis, bring fluency with the dispatch system and radio, cost less and tend to stay longer, and the brief cites Elk Grove, California, which staffs its center entirely with civilians and gives lower turnover as one reason. For a small room, a mostly civilian team with at least one person who has worked the street is a sensible starting point, and job classification should be settled with HR and the unions before the position is posted.

Whatever mix an agency chooses, two things about keeping those people apply to every room. APCO International's Project RETAINS found that supportive supervision, support from co-workers and feeling recognized are the strongest predictors of whether emergency communications staff stay, and the same labor pool fills real-time crime centers. And the people making these decisions see violent events, often live and then again during review, which the Office for Victims of Crime describes as a source of vicarious trauma for anyone repeatedly exposed to violence, so access to peer support and a debrief after serious incidents belong in the plan from the start.

How VIDIZMO keeps the decisions manageable

In AI Live Insight, rules are set per camera, with zones for loitering, intrusion, crowd count or direction of travel and a severity and confidence threshold for each detection class, so a closed park at night can be tuned differently from a busy transit stop and the alert volume stays within what the people on duty can handle. VIDIZMO works closely with the agency to calibrate the models, thresholds and rules to its own cameras and scenes, and the pilot measures the resulting alert volume on the agency's own footage, which is the number the worksheet above needs.

Alerts reach people in the systems they already use, through per-camera email with a snapshot and through webhooks to a dispatch platform, a messaging tool or an SMS service that texts the sergeant on shift. Whoever does the verifying can also work from the operator dashboard, which brings forward the cameras with active alerts and counts open alerts by severity, so nobody cycles through hundreds of feeds.

Our real-time situational awareness page shows how this works on existing cameras.