Taylor Police Department in Michigan: Pioneering AI and Robotics in Policing

In Taylor, Michigan, the police department is harnessing cutting-edge artificial intelligence (AI) and robotics to transform its law enforcement operations. This suburban Detroit community’s officers have become early adopters of technologies like autonomous drones, AI-powered “robot dogs,” and automated license plate recognition systems – tools that many larger agencies are only beginning to explore. Taylor Police Chief John Blair calls this trend “the evolution of police work,” as new devices can arrive at scenes before officers, provide crucial information, and enhance safety. By integrating these innovations, the Taylor Police Department (TPD) has significantly improved response times, officer safety, and investigative efficiency. While policing in the 21st century faces staffing challenges and rising demands, Taylor’s embrace of AI and robotics offers a case study in how technology can augment traditional policing methods to better serve the community. This article examines how the Taylor Police Department has implemented these high-tech tools – from autonomous drones to robotic K-9 units – and highlights the tremendous benefits they have brought to daily operations.

A Culture of Technological Innovation in Taylor PD

The Taylor Police Department has developed a reputation in the Downriver region of Michigan as a leader in law enforcement innovation. “Taylor’s been known as a leader of innovation throughout this area as far as our drone units and different equipment that we’ve led the way with,” noted Lt. Jeff Adamisin, who oversees much of the department’s technology. This progressive mindset set the stage for TPD to be first in Michigan with certain advancements – including deploying the state’s first police robot dog and one of its first autonomous drone programs. Embracing new tech is partly born out of necessity; like many U.S. departments, Taylor faces staffing shortages. The department is funded for 86 officers but currently has only 74 on staff. “Finding them is tough,” Adamisin admits. In this context, technology serves as a force multiplier to fill gaps. Tools such as the Flock Safety camera system were adopted when opportunities arose, because they can amplify the reach of a limited force. “We don’t have the personnel that we’ve had through the years…this technology helps us out,” Chief Blair explained, emphasizing the need to “work smarter”. By capitalizing on innovations, Taylor’s officers gain extra “eyes,” faster situational awareness, and safer ways to handle dangerous jobs – all without straining an already thin roster.

Importantly, Taylor’s leadership has paired its tech-forward strategy with community engagement and transparency. City council and public backing were secured for major initiatives, and officials have been upfront about how the tools will be used. For example, Chief Blair has reassured residents that autonomous drones will not be used for random surveillance, only for responding to active incidents. And when adding a robot “canine,” the department even involved local students in a contest to name the new device, signaling that the technology is meant to serve – not spy on – the community. This proactive communication has helped maintain public trust as Taylor moves policing further into the digital age. While law enforcement agencies nationwide grapple with adopting AI responsibly, Taylor’s approach shows how thoughtful implementation and outreach can make advanced tech a welcome ally in public safety.

Deploying the RADDOG Robotic Police Dog

One of Taylor’s most groundbreaking moves was adding a robotic police dog to its ranks – an AI-powered, four-legged robot known as the RADDOG 2LE. In early 2024, the Taylor Police Department became the first law enforcement agency in Michigan (and the first city in the nation) to deploy this type of robot for police work. On March 19, 2024, the department unveiled the RADDOG 2LE, a black mechanical “dog” with a tablet-like screen for a head, eliciting immediate media attention. Manufactured by Robotic Assistance Devices (RAD), a subsidiary of Detroit-area firm AITX, RADDOG 2LE is a state-of-the-art quadruped robot designed specifically for law enforcement support. Taylor acquired the robot on a one-year trial lease for about $32,500 (funded entirely through federal asset forfeiture funds, at no direct cost to taxpayers). The robot dog’s mission is straightforward yet critical: to enter high-risk situations so human officers don’t have to.

RADDOG’s Features and Capabilities

Despite its playful moniker, the RADDOG 2LE is a serious piece of equipment built to keep officers and citizens safe. Key features of Taylor’s robotic dog include:

Advanced Optics: Equipped with five cameras providing 360° surveillance and streaming video, giving officers eyes on a scene from multiple angles. A forward-facing camera provides a direct visual link, even in low-light or obscured conditions.
Two-Way Communication: A built-in speaker and microphone establish a two-way audio/video channel between police and suspects or victims. As Chief Blair described, “It puts us face-to-face with the person or situation without a risk of harm. It can act almost like Zoom” – essentially allowing negotiation or dialogue via the robot. Officers can see and speak through RADDOG from a safe distance, and the individual can talk back to the machine as if conversing with an officer.
Mobility and Agility: Roughly the size and weight of an adult Standard Poodle, the quadruped robot is nimble enough to navigate tight or treacherous spaces that might be inaccessible to humans. It walks, turns, and can even traverse uneven terrain or stairs, all while maintaining balance. At the Taylor unveiling, observers noted the robot emitted a soft whirring sound as it scooted back and forth in demonstration.
Remote Operation: The RADDOG is controlled by an officer via a laptop interface. Using a wireless connection, operators can drive the robot, pan its cameras, speak through it, and activate pre-programmed functions. In the future, more autonomous behaviors may be introduced, but initially a human pilot keeps the robot on task – much like a remote-controlled drone on the ground.
Non-Lethal, Defensive Tool: Notably, Taylor’s robot dog is unarmed – it carries no weapons. Instead, it is a “situational, defensive tool” focused on reconnaissance, communication, and de-escalation. Its value lies in what it sees and hears, not in use of force. (That differs from a real K-9 or even some bomb-disposal robots that can carry disruptive devices.) Taylor officials have indicated they may explore adding accessories like sensors or a robotic arm to expand RADDOG’s capabilities over time, but the core purpose is to “be our eyes and ears” in dangerous situations, as Chief Blair put it.

These features make RADDOG a versatile asset for law enforcement scenarios. It can climb into an attic or crawl space where a suspect might hide, peek around a corner during a standoff, or enter a room ahead of officers to gauge a threat – all while officers remain behind cover. Essentially, the robot can go where it would be too risky to initially send a person. “The robotic dog gives its user a vision that may not be available without human risk,” explained Lt. Adamisin, underscoring how it extends an officer’s situational awareness without exposing them to harm.

Safer Responses to Dangerous Situations

Taylor police intend to deploy the RADDOG in high-risk incidents, particularly those involving armed or barricaded suspects where negotiation and eyes-on intel are needed. “It’s an officer safety tool and a de-escalation tool,” Chief Blair emphasizes. For example, if a person barricades themselves in a house or is holding hostages, “we can send this dog in to communicate” with them instead of immediately risking an officer’s life. Through the robot’s cameras and speaker, negotiators can attempt dialogue and assess the suspect’s condition remotely. This not only buys time and minimizes the immediate threat to police, but it can also calm the situation – a robot’s presence may feel less provocative than a team of SWAT officers breaking down a door. RAD markets the RADDOG as a “de-escalation tool” that is safer than sending an officer into an armed situation. Taylor’s experience so far supports this: “Instead of putting that officer at risk and possibly escalating a situation, we can send our robotic dog to take a look,” Chief Blair said. The robot can gather crucial intel – layout of the interior, suspect’s location and state, presence of weapons or victims – all without any person coming to direct harm.

This capability is more than theoretical. Taylor had multiple critical incidents in early 2024 where RADDOG could have made a difference had it been available just a bit sooner. “The device could have been used four or five times in the past month alone,” Chief Blair noted at the March unveiling. “We had a couple barricade situations; we had an individual who was inside of a house and shot at our officers.” In those dangerous encounters, the robot dog might have allowed officers to observe or communicate with the shooter without exposing themselves to gunfire. Going forward, any similar scenario is exactly when RADDOG will get the call. Police also envision using it for scenarios like an active shooter in a school or a suspect hiding in a large industrial facility, where sending robotics in first could save lives on both sides of the badge.

Even in non-criminal emergencies, the robotic K-9 can prove useful. It could scout a building after a structural collapse or hazardous material incident to find injured victims – tasks where robots have already shown value elsewhere. (In fact, New York City firefighters deployed a robot dog to search the rubble of a collapsed parking garage in 2023, and the technology helped locate survivors without endangering rescue crews.) Taylor’s RADDOG could perform similar search-and-rescue duties if ever needed, supplementing its primary law enforcement role.

Training, Community Reception, and Future Development

Since taking delivery of the RADDOG in March 2024, Taylor officers have been training extensively with their new mechanical partner. The vendor’s team provided initial demos and two trial runs in simulated scenarios over the winter. These practice sessions allowed the SWAT team and patrol officers to get comfortable operating the robot and to integrate it into tactical training moving forward. By late March, TPD officials expected training to be completed and the robot fully deployable in the field. They plan to collect data on each deployment – what worked, what didn’t – to continually improve tactics. “We’re going to be collecting real empirical information, use cases and experiences,” said AITX/RAD CEO Steve Reinharz. The company will share findings with Taylor and use them to refine future iterations of the RADDOG. In essence, Taylor is a pilot site helping to shape how robot police dogs might be used elsewhere. “The Taylor PD plans to exhaustively place RADDOG in real-world situations and share their findings,” Reinharz noted, calling the partnership “a significant milestone in the evolution of law enforcement technology”.

So far, the community’s response has been largely positive – marked more by curiosity and excitement than concern. The novelty of a robot “dog” on the police force garnered plenty of local news coverage, introducing the public to the device’s purpose. To personalize the machine, the department invited schoolchildren to help choose a name for the robot, underscoring that it’s a friendly helper, not something to fear. “Everybody’s watching what we do with it and the excitement locally has been very good,” Lt. Adamisin reported in late February. He added that most people recognize the logic: “I think a lot of people would rather risk a robot getting shot or damaged than an officer”. City officials also tout that the program isn’t siphoning resources from other needs – using federal forfeiture funds meant no extra burden on taxpayers. Of course, a few skeptics wonder if this is the start of “RoboCop” or an over-militarization of local police. But Taylor’s leaders stress that the robot will not replace human officers. “It’s not meant to replace an officer, it’s meant to support officers in the mission to protect the community,” Adamisin explained, clarifying the robot is just another tool in the toolbox. In fact, RADDOG is always deployed with officers operating it, not on its own. Mayor Tim Woolley has praised the initiative as “a great way to keep our residents and police officers safe. That’s the main goal.”

Moving forward, Taylor hopes to expand the RADDOG’s capabilities in collaboration with the manufacturer. One idea is attaching a robotic arm or gripper, which could allow the dog to open doors, pick up objects (like suspicious packages or weapons), or even perform basic first-aid delivery (such as bringing a phone or medical kit to an injured person). Additional sensors, like thermal imaging or gas detectors, could be added to help in fire or hazmat scenes. Taylor is working directly with RAD’s parent company, AITX (based in nearby Royal Oak, MI), on these potential upgrades. “We will continue to invest in improving this technology with an eye toward being budget friendly,” said Reinharz, noting their goal is to eventually make a version of RADDOG that is “every law enforcement member’s best friend and riding in every car on every patrol”. That future may be years off, but Taylor’s early adoption is helping pave the way. For now, the focus is proving the concept: demonstrating that a robot dog can effectively defuse crises and save lives in a mid-sized American city. If the first year yields positive results – measured in safely resolved standoffs or injuries prevented – Taylor could extend the lease or acquire additional units. “It may take time, but this concept has tremendous potential, and it starts today,” Reinharz said at the rollout. By pioneering this technology, the Taylor Police Department is indeed setting a precedent for modern policing that other departments in Michigan and beyond are watching closely.

Eye in the Sky: Autonomous Drones for Rapid Response

Before acquiring its robot dog, Taylor was already leading the pack in another arena of police robotics: unmanned aerial vehicles, or drones. The department stood up a drone unit in recent years and has used pilot-operated drones for tasks like searching for missing persons, documenting accident scenes, and surveying large crime scenes. Building on that foundation, Taylor has now become one of the first police departments in Michigan to deploy autonomous “Drone as First Responder” (DFR) technology. In June 2025, TPD officially launched a new program using rooftop-launching quadcopter drones that can take off on their own and race to emergency calls, often arriving within 60–90 seconds – well before officers on the ground. “Anywhere in the city, that drone is going to be able to get there within a minute, minute and a half,” Lt. Adamisin said, highlighting a game-changing advantage for swift response.

The concept of DFR is to have drones patrolling the skies or on standby to be dispatched to incidents just like a patrol car would, but much faster. Taylor’s system involves two drones housed in weather-proof “drone ports” on the roof of police headquarters, plus a third drone designated for indoor use. When a 911 call comes in, officers in the dispatch center can quickly evaluate if a drone could be useful – for instance, a report of a traffic accident, a suspicious person, or a possible crime in progress. With a few clicks on a computer map, the operator drops a pin on the incident location and launches the drone remotely. The drone automatically takes off from its rooftop base, climbs to a preset altitude, and flies itself to the GPS coordinates of the call. “It’s direct-line flight. They travel 45 mph,” Chief Blair said of the drones, meaning they take the most efficient path over buildings and roads to get on scene fast. Upon arrival, the drone begins recording live video of the scene, which streams back to dispatchers and any officers en route on their vehicle laptop screens.

Capabilities of Taylor’s Drone Program

The Taylor Police have carefully configured their drone system for maximum practical benefit. Notable aspects of the program include:

Rapid Autonomous Deployment: The system integrates with dispatch so that a drone can be airborne within seconds of an address being entered. There’s no need to wait for an officer to physically retrieve and launch the UAV. One click from indoors, and the drone is on its way, responding autonomously to the GPS location provided. This drastically reduces response times for initial visual assessment.
High-Speed, City-Wide Coverage: The drones can fly up to ~45 miles per hour and take a “direct line” route. With Taylor covering about 24 square miles, that means the farthest corner of the city is only ~1–2 minutes away by drone. In many cases, an eye in the sky can arrive even before the first 911 dispatcher finishes taking the caller’s information. This immediacy gives officers real-time awareness (via the drone’s video feed) of what they’re heading into.
Real-Time Intelligence Gathering: As the drone hovers or circles the target location, it beams live video to officers. They can observe crucial details: How many people are present? Are weapons or dangerous conditions visible? Is the incident large-scale or minor? “It gives us an eye in the sky, a huge advantage to our officers responding and to those who are on scene,” Chief Blair said. Essentially, the arriving officers get a virtual scout arriving ahead of them to survey the situation.
Indoor Search Capability: Uniquely, Taylor also obtained a small “interior drone” equipped with 3D imaging and two-way communication. This handheld-sized drone can fly inside buildings – useful for clearing houses in a burglary call or searching classrooms during a school lockdown. It streams a 3D map of indoor spaces and, like the RADDOG, has a speaker and mic for communicating with people inside. Officers can thus remotely look and talk inside a structure if needed, all while stationed safely outside.
Operator Oversight with Assisted Flight: While the drones can take off, fly to scene, and return to base largely on their own, Taylor’s protocol is to have trained officers monitoring each flight from the command center. The drones are “autonomous, not totally autonomous,” Lt. Adamisin explained – humans will handle the launch command and can intervene if needed. For the most part, however, the navigation is handled by onboard AI and GPS. The system also checks for legal airspace and weather conditions automatically before launch, ensuring safety and FAA compliance.
Secure Return and Recharge: After completing a mission, the drones fly back to headquarters and land on their rooftop pads. The pad station then recharges the drone’s battery, readying it for the next call. With two outdoor drones, Taylor can alternate their use to cover back-to-back incidents, while one recharges. Each battery provides roughly 30-40 minutes of flight time, sufficient for most call responses (and as police note, not enough endurance for any prolonged “surveillance” usage even if they wanted to do that).

Improving Response Times and Officer Safety

The benefits of Taylor’s drone program were apparent from day one. By arriving on scene so quickly, drones can feed critical information to officers before they even arrive. In a recent demonstration, a drone was dispatched to a report of a person unconscious in a park; it arrived in about one minute and relayed that the person appeared to be awake and walking around, saving multiple patrol units from racing there lights-and-siren. In another scenario, involving a reported break-in, a drone’s early peek showed no sign of forced entry, allowing responding units to downgrade their approach. These examples illustrate how drones help allocate resources more efficiently – officers can gauge from the live feed whether they truly need to rush or if a situation is under control. Over time, this should improve response times to genuine emergencies while reducing unnecessary risks in lower-priority calls.

For serious crimes in progress, the advantage is even more pronounced. Chief Blair gave examples of incidents the drones could assist: “Maybe potentially a homicide scene, someone that’s barricaded inside holding someone hostage, [or] a very large disturbance, large fight,” he said. In such cases, getting eyes on the scene 1–2 minutes sooner can be lifesaving. Officers can formulate a tactical plan with foreknowledge of suspect locations or dangerous elements, and they might even use the drone’s loudspeaker to announce their presence or warn a suspect to surrender. If an armed suspect is trying to flee, the aerial view can track their movement for coordinating containment by ground units – all without putting an officer in the suspect’s direct path during those first critical moments. Officer safety increases because the drone might spot an ambush or weapon before officers walk into it. As one Detroit officer, who was wounded on duty in the past, commented about Taylor’s drones: “A device like that… doesn’t have to worry about getting hurt. It’s nice to know those are up there helping you, getting you maybe different images, increasing the safety of what you’re doing every day in your job.”

Additionally, drones can aid the public’s safety by arriving so fast. For medical calls like accidents or heart attacks, a drone can start assessing the scene and relaying information to EMTs or fire crews. In police chases, a drone spotting a suspect’s vehicle could allow ground officers to coordinate a safer interception ahead, rather than engaging in a high-speed pursuit from behind. Taylor’s chief succinctly described the drone program as “a time-saver [and] officer safety [tool], [with] citizen safety all rolled up into one.” By mid-2025, Taylor had two patrol cars less on the road due to staffing – but in effect, two drones in the air helping cover the slack. This technology offers a way to do more with fewer officers, something many departments today desperately need.

Privacy and Community Considerations

Whenever police deploy cameras in the sky, community concerns are inevitable. Taylor’s police leadership has been keenly aware of this and has taken steps to reassure the public that the new drones will not infringe on privacy or be misused. “The technology is not used for surveillance – that is not the case, I can assure you,” Chief Blair told residents emphatically. He explained that the drones’ limited battery (about 40 minutes) and the department’s lack of interest or staffing for any mass surveillance make it infeasible to use them except for responding to active calls. Taylor’s drones are “incident-based only”, Blair said – they launch when there’s a 911 call or officer request, and they don’t randomly patrol without cause. The department has also likely established policies (in line with FAA rules and state law) that prohibit recording beyond what’s necessary and restrict storing drone footage unless it’s evidence of a crime.

These assurances appear to have been effective. The drone initiative, announced through local news and city council meetings, met little public resistance. Community members seem to recognize the value in quicker emergency response and the life-saving potential of the drones. Just as with the robot dog, Taylor officials stress that the drones are there to support officers and keep everyone safe, not to replace human policing or intrude on citizens. They cite the program’s positive outcomes and transparency to build trust. As Lt. Adamisin said, the department is “very proud about the technology we’re trying to utilize here” to protect the community. By addressing privacy questions head-on and demonstrating drones’ tangible benefits (like video of a suspect with a gun on a roof that helped resolve a situation peacefully), TPD has fostered public support. In fact, Taylor’s success with autonomous drones is already inspiring interest from other Michigan police agencies, showing that when handled openly and responsibly, police drones can gain community acceptance as a public safety tool.

AI-Powered Surveillance: License Plate Recognition Cameras

Not all of Taylor’s high-tech helpers are as visible as a robot dog or buzzing drone – some quietly watch over the city from fixed positions, automatically scanning for criminals. One such technology is the Flock Safety license plate recognition (LPR) camera system, which Taylor began rolling out in 2023–2024. These solar-powered, motion-activated cameras, mounted on poles or traffic lights, continuously capture images of passing vehicles and use AI to read the license plates. The system instantly checks each plate against databases of stolen cars, wanted suspects, missing persons, and other hotlists. If a match (“hit”) is found, an alert is sent in real time to officers’ computers or patrol car MDTs. The alert includes the plate number, a photo of the vehicle, and the location where it was spotted. Crucially, the system does not photograph vehicle occupants or reveal any personal identifying details – “We don’t know the race [or] the sex of the driver at all,” Lt. Adamisin noted, addressing potential bias concerns.

Taylor has deployed about 50 Flock “Falcon” cameras around the city at key intersections and entry/exit points. The network cost roughly $150,000, which city leaders saw as a solid investment given the promised payoff in crime reduction. And indeed, the results have been remarkable. According to Lt. Adamisin, within months the Flock LPR system was already helping solve major crimes and recover stolen property. “We’ve had multiple armed robbery suspects identified and arrested due to the Flock LPRs; we’ve [caught] shooting suspects, fraud rings, and [recovered] approximately 60 stolen cars,” Adamisin reported in May 2024. Each alert gives officers a chance to intercept criminals in flight or to gather investigative leads that they might otherwise miss. For example, if a getaway car from a robbery flees the scene, traditional policing would rely on an officer spotting that vehicle by chance. Now, with strategically placed cameras, Taylor can virtually “spot” the car as it passes a choke point and direct units immediately to its location.

Boosting Investigations and Crime Fighting

The integration of AI-driven license plate readers has tremendously helped Taylor’s crime-fighting operations in several ways:

Capturing Fleeing Criminals: Perhaps the biggest benefit is catching suspects who would have otherwise gotten away. In one case, Taylor officers were working with federal Homeland Security agents during the NFL Draft events in Detroit, targeting sex trafficking. They knew a suspect was driving in from a distant city (Brighton, MI). Thanks to the Flock cameras, “we could track that vehicle as it headed [in]. I did not have to deploy a six- or eight-man surveillance crew to follow them…we tracked that vehicle as it came into our city,” Chief Blair recounted. Using a series of LPR hits along the highway, officers safely monitored the suspect’s approach and then arrested him at the meeting location. This avoided both the manpower and risks of tailing the suspect physically across counties. In another instance, a carjacker from out of town was intercepted because a Flock camera hit on the stolen car’s plate the moment it entered Taylor, allowing officers to stop it without a dangerous pursuit. In just a short span, Taylor recovered dozens of stolen automobiles thanks to automatic alerts – each recovery representing a crime solved that might have gone undetected for much longer.
Investigative Leads and Evidence: Even when an alert doesn’t lead to an immediate arrest, it provides valuable data. Detectives can query the system for a suspect vehicle’s sightings to establish patterns (e.g., a burglary suspect’s car was near the scene of three incidents). In a shooting case, Flock cameras identified a suspect vehicle fleeing at 2 a.m., which helped generate a lead on possible suspects based on the car’s registration. LPR data has essentially become a digital witness that can place suspects at a certain place and time, often vital for building a case. Because the system timestamps and photographs each hit, it provides court-admissible evidence showing, for example, that a stolen car was in Taylor on a given night.
Force Multiplication: The LPR cameras act as “extra officers” scanning the streets 24/7. “The cameras have become a force multiplier for the department,” noted the CBS Detroit report. They tirelessly monitor for wanted vehicles even when no officer is around. Given Taylor is down over a dozen officers from full staffing, these automated sentinels help cover more ground than the human team alone could. As Chief Blair explained, he simply doesn’t have the manpower to conduct long surveillance or stakeouts on suspects. Now he doesn’t need to – the AI cameras quietly do the job, and “it can be very dangerous to do surveillance” in person anyway. By offloading plate-watching duties to algorithms, Taylor’s limited officers can focus on responding to the actionable alerts and other community policing tasks. The technology essentially patrols the city’s perimeters in the background, ensuring that any known “bad actors” who enter will be noticed.
Timely Interventions: When a Flock alert pops up, patrol officers can immediately reposition to intercept the vehicle in question. The alert shows a map of exactly where the car was spotted, allowing units to set up ahead or converge quickly. This led to swift arrests of several armed robbery suspects who thought they’d escaped the scene – only to be surprised by Taylor units who got the alert and cut them off a few miles away. Quick interventions like this help prevent suspects from committing further crimes or engaging in dangerous pursuits. In essence, the system enables smarter deployment of police resources in real time.
Targeted Enforcement Without Profiling: An important aspect is that the LPR system focuses on objective data (license plates linked to crimes) rather than subjective characteristics of drivers. The cameras intentionally do not capture faces or personal descriptors. This means officers respond to hits based on a vehicle’s identifier and known offense (stolen car, warrant, etc.), not based on who is in the car. It helps avoid bias – the technology can’t “see” race or gender – and ensures enforcement is directed only at vehicles connected to illegal activity. This approach can increase community confidence that the tech is used fairly, as it’s not randomly surveilling everyone, only flagging those already tied to unlawful acts.

The success stories are piling up. Taylor Police report that multiple armed robbery suspects and even shooting suspects have been apprehended directly thanks to LPR alerts. In one quarter, about 60 stolen vehicles were recovered – a huge number for a city of 63,000 – which undoubtedly also led to related arrests (car thieves, for instance). Additionally, during the NFL Draft week sting operation mentioned, seven individuals who came to Taylor expecting to exploit children were instead met with handcuffs, with the LPR system aiding in their capture. Each of those arrests potentially prevented further victimization. Chief Blair summed up the impact: “This system is locating wanted people, bad people in society, and it’s giving us another set of eyes,” he said gratefully. In other words, the Flock cameras quietly watch over the community, spotting dangerous actors so officers can swiftly take them off the streets.

Integrating Technology into Daily Policing

Adopting the Flock LPR system required careful planning and policy-setting by Taylor Police. Officers had to be trained on the software that delivers alerts to their in-car laptops and how to respond appropriately. The department likely established protocols for confirming an alert (for example, verifying the license plate number) and coordinating response (so that multiple units don’t all rush separately). By now, responding to a Flock hit has become a routine part of Taylor’s policing. Officers start their shift by logging into the Flock system, and throughout the day they remain ready to react if an alert comes over. Detectives periodically review the data for ongoing investigations, and administrative staff ensure the cameras are maintained and software updated.

One notable aspect is cross-agency collaboration: the value of LPR extends beyond Taylor’s borders. The cameras can notify Taylor officers of wanted persons from other jurisdictions passing through, and conversely, if Taylor enters a plate linked to a local crime, other nearby cities using Flock might catch that plate in their area. This regional sharing helped in a case where a fraud ring traveling through multiple Metro Detroit cities was identified – Taylor got a hit on their plate and coordinated with neighboring departments to arrest the suspects, unraveling a string of scam incidents. It shows how AI tools can foster cooperative, intelligence-led policing across what used to be siloed jurisdictions.

As with any surveillance-related technology, the use of LPR cameras raises privacy questions. Some community members may worry about “Big Brother” monitoring movements or storing data on innocent drivers. Taylor has addressed this by clarifying data retention policies (Flock data is typically deleted after 30 days unless tied to a criminal case) and emphasizing the specificity of its use. They publicly stated that images on Google or social media showing unrelated content are not from their systems, and that no personal data is being collected about law-abiding citizens. The focus is strictly on license plates associated with crimes. So far, there has been little public pushback, likely because the immediate crime reduction benefits are evident. Successes like recovering a stolen car and returning it to its owner within hours help justify the program. Additionally, the cost – $150k for 50 cameras – is far less than hiring additional full-time officers, making it fiscally attractive as well. In a city that has seen budget and staffing constraints, using AI cameras to cover more ground is a pragmatic solution.

In sum, the Flock LPR system has seamlessly integrated into Taylor’s policing toolkit. It runs quietly in the background but yields loud results in terms of arrests and deterrence. Criminals now know that if they drive into Taylor, there’s a good chance they’re being electronically watched – and if they’re wanted, the police will soon be on their tail. That serves as a strong deterrent and pushes criminals to think twice about operating in the city. The Taylor Police Department’s experience mirrors a broader trend: across Michigan, use of drones and LPR cameras by law enforcement has risen dramatically in recent years (drone usage jumped from 3% of agencies in 2015 to 31% by 2024), even as more controversial AI tools like facial recognition remain limited. By focusing on proven technologies like license plate readers, Taylor has struck a balance – leveraging AI for clear public safety gains while avoiding areas of major public concern.

Operational Impact and Community Benefits

Taylor’s strategic adoption of AI and robotic technologies is yielding tangible improvements in police operations and community safety. These tools – the RADDOG robot, autonomous drones, and LPR cameras – each address different challenges, but together they enhance the department’s capabilities in complementary ways. The overall impact has been profoundly positive:

Enhanced Officer Safety: Above all, these technologies keep officers out of harm’s way in the most dangerous situations. Whether it’s a robot dog confronting an armed suspect in a barricaded house or a drone scouting a volatile scene from above, Taylor police can now “put [technology] between officers and danger” as a first layer of response. This reduces the likelihood of officer injuries or worse. As one injured veteran officer observed, knowing a robot or drone can take the initial risk “increases the safety of what you’re doing every day” on the job. And it’s not only officer safety – by defusing situations more peacefully and avoiding high-speed chases or drawn guns, suspects and civilians are safer as well. Fewer confrontations escalate to violence when a machine can be sent in first to negotiate or locate a suspect. It’s notable that Chief Blair believes these tools can even “prevent officers from having to use serious force, including deadly force” in some cases by enabling alternatives to an armed showdown.
Faster Response and Situational Awareness: Time is critical in emergencies, and Taylor’s drones and automated alerts have dramatically cut response times. In many instances, drones now arrive on-scene before 911 callers have hung up, providing immediate eyes that were never available to dispatchers before. This real-time intelligence means officers heading to a call already know what to expect – a huge advantage for effective and safe resolution. The first minutes of an incident often dictate its outcome; with AI assistance, Taylor PD makes those minutes count. For example, a drone feeding live video of a large brawl allows the police to call for exactly the backup needed and stage responders at the right locations. An LPR alert about a fleeing felon allows patrols to position ahead of time rather than racing blindly. The net effect is quicker, more informed decision-making in the field.
Force Multiplier Amid Staffing Challenges: Technology can’t replace human police, but in Taylor it has certainly augmented them. With staffing below desired levels, the department relies on these force-multiplying effects to sustain service quality. Each autonomous drone sortie is like an extra officer on scene doing reconnaissance. Each camera alert is akin to a vigilant patrol unit spotting a criminal by chance. “It’s giving us another set of eyes,” as Lt. Adamisin put it. In quantitative terms, the 50 LPR cameras monitor far more cars each day than a handful of traffic officers could; the drones can effectively patrol the whole city faster than any cruiser. This helps offset the reduced headcount and ensures that critical duties (like traffic enforcement, searches, or surveillance) don’t fall through the cracks. As a result, despite being under-strength, Taylor PD has improved clearance rates and interdictions because the tech helps catch what officers alone might miss.
Improved Crime Solving and Prevention: The numbers speak to a significant crime-fighting boost. Dozens of criminals taken off the streets, from car thieves to would-be child predators, can be directly credited to the new technologies. That means fewer crimes in the community – stolen vehicles returned to owners, robbery sprees halted, potential violent encounters averted. Moreover, the presence of these tools likely deters crime. Just as a burglar might avoid a house with a visible alarm system, criminals who know Taylor has robot dogs, drones, and plate readers might choose easier targets elsewhere. It’s hard to quantify crimes prevented, but the deterrent effect is real when technology raises the perceived risk of getting caught. Taylor’s reputation as a tech-savvy, “hard target” jurisdiction is growing, which over time contributes to public safety.
Cost-Effective and Resource-Saving: In an era of tight municipal budgets, Taylor’s investments have shown good return on investment. A $32k robot dog lease and a $150k camera system are minor expenses compared to salaries and benefits for additional officers or the losses incurred from unchecked crime. Additionally, deploying a robot or drone can at times save costly specialized callouts – for instance, resolving a situation without needing a multi-agency SWAT activation or avoiding property damage that might occur in a tactical raid. The proactive arrests from LPR alerts can prevent protracted investigations later. All told, while these technologies do incur maintenance and training costs, they likely pay for themselves by streamlining operations and preventing incidents that have high societal costs.
Community Trust and Engagement: Interestingly, Taylor has managed to introduce these advanced tools while largely maintaining or even improving community relations. By emphasizing the life-saving aspects and involving citizens (like the robot naming contest and clear communications about drone use), they frame technology as protecting the community, not oppressing it. Residents have seen the upside – safer streets, faster emergency responses, and even the novelty of a friendly robot at events – without feeling their privacy or liberties are being trampled. The department’s transparency, such as promptly addressing the prank where Google searches showed unrelated marijuana photos on their listing (an odd incident they resolved with public explanation), demonstrates a commitment to honesty and accountability in all tech matters. This openness likely makes the public more receptive to innovations. So far, Taylor has avoided the backlash that some big cities faced with similar tech (e.g., NYPD’s initial robot dog deployment met public outcry in 2021), perhaps because they learned from those examples and rolled out their program more thoughtfully. The result is a community that, by and large, feels safer and supports the police’s high-tech initiatives.

In summary, the integration of AI and robotics into Taylor’s policing has tremendously helped the department’s operations across the board. It has made officers safer, responses quicker, enforcement smarter, and the community more secure. Taylor’s experience demonstrates that when implemented with care, technology can amplify the core mission of law enforcement: to protect and serve. The department’s motto might not have changed, but its methods certainly have – and the city is seeing the benefits first-hand.

Future Outlook and Conclusion

As the Taylor Police Department looks ahead, it aims to build on the successes of its AI and robotics initiatives while continually evaluating and refining their use. The next year will serve as a proving ground for the RADDOG robot dog – its performance in real incidents will be closely monitored and shared. If it consistently helps defuse dangerous situations, Taylor could seek to extend the program or even purchase additional units (perhaps one per SWAT team or per shift) as costs come down. The collaboration with AITX/RAD means Taylor’s feedback might influence the next generation of police robots, tailoring them more to municipal needs. It’s conceivable that future models might feature modular add-ons (arms, chemical sensors, etc.) and greater autonomy, making them even more useful. Taylor officers are effectively helping to write the playbook for robotic assistance in policing, and other departments in Michigan are watching their results. “I truly foresee a future where a RADDOG accompanies every police cruiser on every call,” said CEO Steve Reinharz – an ambitious vision, but one that Taylor is bringing closer to reality.

The drone program, too, will likely evolve. In time, Taylor could expand beyond the initial two outdoor drones, perhaps placing drone launchpads in different parts of the city or on other city buildings to cover even more area. As regulators gradually ease restrictions, the drones might one day be allowed to patrol preemptively or respond outside of direct visual line-of-sight with full autonomy, which would unlock even more potential. For now, TPD will focus on using the drones for a wider array of calls and demonstrating quantifiable benefits (such as reduced response times, better outcomes in emergencies). If those metrics impress city officials and residents, funding could be allocated to sustain and grow the program. Taylor has essentially become Michigan’s pilot site for DFR (Drone as First Responder) in policing – success here could lead to a wave of similar programs in other cities. In fact, Taylor has collaborated with at least one other department to share lessons on starting an autonomous drone unit. This leadership role is a point of pride for the department, aligning with their identity as innovators.

On the data and AI side, Taylor will continue leveraging analytics to fight crime intelligently. The Flock LPR system will remain a staple, and the department may integrate additional databases (like warrants or Amber Alerts) to further capitalize on it. As crime patterns shift, they can reposition cameras or add new ones to high-traffic locations. Given the system’s success, the city might invest in more AI tools – for instance, gunshot detection sensors, or predictive crime mapping software to allocate patrols (noting that predictive policing is used sparingly in Michigan as of now). Taylor has shown it will carefully consider tech that provides clear value. One area to watch is AI analysis of body-worn camera footage – an emerging tool that some agencies are testing to automatically flag incidents or assist in report writing. With Taylor’s focus on transparency and accountability (they already equip all officers with Axon body cameras), adopting AI to review those videos could be a logical next step to improve oversight and training. If they do, it would further underscore their status at the forefront of policing technology.

Crucially, Taylor PD appears committed to balancing innovation with responsibility. As these programs progress, the department will need to maintain strong policies, training, and community dialogue to address any issues that arise – whether it’s a malfunctioning drone or concerns about surveillance. Thus far, they’ve navigated that balance well. “Transparency, oversight, and community engagement will be critical as agencies grapple with the ethical and operational challenges posed by AI,” a University of Michigan report noted broadly, and Taylor’s approach reflects that wisdom. Deputy Chief Mike Lividini’s handling of the Google image prank – promptly alerting the public and working with tech companies to fix misrepresentations – exemplifies the department’s dedication to managing its public image and digital footprint conscientiously.

In conclusion, the Taylor Police Department’s foray into AI and robotics showcases the promising future of tech-assisted policing. In a mid-sized city with limited resources, these tools have already made a dramatic difference, from disarming dangerous suspects without bloodshed to plucking criminals off the streets through algorithmic alerts. The phrase “taking a bite out of crime” took on new meaning when Taylor’s mechanical K-9 reported for duty, and the sky is literally not the limit as drones become first responders. Far from a sci-fi gimmick, these technologies are proving their worth as practical solutions to age-old policing challenges. Taylor’s officers now have backup from tireless machines that never blink, hesitate, or fatigue – allowing the humans to focus on compassionate, community-oriented policing where it matters most, and to make better-informed decisions under stress. As other departments consider similar upgrades, they can look to Taylor as a model of how to do it right: secure the funding creatively, involve the community, set clear usage policies, and measure the outcomes. The early returns from Taylor indicate that AI and robotics, used wisely, can tremendously help law enforcement serve and protect. In the city of Taylor, the future of policing has arrived – and it’s making both the public and the police safer than ever.

References

Prestininzi, Jenna. “Robotic dogs to join Taylor police force.” Detroit Free Press, 29 Feb. 2024.
Aguilar, Louis. “Taylor Police debuts robot police dog.” The Detroit News, 19 Mar. 2024.
Sherman, Jolie. “Taylor police launch drone program to improve officer safety and response times.” WXYZ Detroit, 12 June 2025.
Gutierrez, Andres. “Metro Detroit police department receives new robot dog.” CBS News Detroit, 19 Mar. 2024.
Gutierrez, Andres. “Taylor police using hi-tech ‘Flock’ camera system to track criminals.” CBS News Detroit, 29 May 2024.
Meyers, Elle. “Taylor police unveil department’s first autonomous flight drones.” CBS News Detroit, 9 June 2025.
Chen, Angela. “Taylor Police Department in Michigan Pioneers Use of Robot Dog ‘RADDOG 2LE’ to Enhance Officer Safety and Crisis Intervention.” Hoodline, 20 Mar. 2024.
Robotic Assistance Devices (RAD). “RAD Makes History with First Robotic Dog Deployed to Taylor Police Department.” RAD Security (Press Release), 20 Mar. 2024.
Artificial Intelligence Technology Solutions (AITX). “AITX’s RAD Announces First Municipal RADDOG Adoption.” AITX Press Release, 8 Feb. 2024.
Putman, Joanna. “Mich. PD adopts RADDOG robot dog.” Police1, 9 Feb. 2024.
BABL AI News. “Michigan Law Enforcement Expands Tech Use, but AI Adoption Remains Uncertain.” BABL AI, 1 May 2025.

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