Can Video Analytics Eliminate Risks Involved?

Forklifts mays not have eyes, but they’ve got a serious blind spot problem – literally!

Forklifts are essential in warehouses, industrial facilities and construction sites. But they come with one of the most persistent safety threats on the ground – “blind spots”. From zigzagging through tight warehouses aisles to reversing with pallets piled sky-high, these industrial workhorses often lead to near-misses, property damage, and in the worst cases, even threatening accidents. Traditional safety tools like beepers and mirrors try their best, but they are no match for a distracted worker or a pallet that is blocking the line of sight.

So here the real question arises: can video analytics give forklifts the super-vision they desperately need? Let’s zoom in.

Forklifts blind spots aren’t just minor visibility gaps; they are high-risk zones where danger often goes unnoticed until it is too late. Blind spots are an unavoidable design flaw, created by the very parts that make forklifts functional: the mast, the load, and the frame.

Forklift blind spots occur when the operator’s field of vision is obstructed by the structure of the forklift, the load that it carries, or the environmental factors within jobsite. Operators often have to rely on instinct or limited tools to “guess” what they can’t see, which is a risky gamble in fast-moving industrial zones.

Forklift blind spots aren’t static, they shift depending on load height, turning radius, and even lighting conditions. A forklift that is clear on one side while unloaded can turn into a moving hazard once it is stacked with materials. Add in unpredictable elements like low visibility corners, tight aisle spacing, or pedestrian movement, and the risks multiply. In such dynamic spaces, even a momentary lapse in visibility can turn routine operations into dangerous encounters, making it crucial to rethink how visibility is supported in real-time.

Forklift blind spots aren’t random; they consistently obstruct critical zones that operators rely on for safe manoeuvring. Here’s where visibility tends to disappear:

• Front View (Especially When Loaded): A lifted pallet or bulky cargo can completely obscure the operator’s entire forward field of vision.

• Side Aisle Gaps: Working in tight warehouse aisles can limit side visibility, making it hard to see nearby co-workers or other equipment moving in parallel.

• Rear Periphery: Rear visibility, especially around the corners, is often limited, creating a hotspot for reversing accidents.

• Under the Mast or Fork Area: Anything or anyone too close to the base of the mast can go completely unnoticed from the driver’s seat.    

Understanding where forklift blind spots are and how they contribute to near-misses and collisions is the first step towards solving the problem. And the next step? Rethinking the tech that can be used to deal with them. 

Forklifts weren’t exactly designed with a panoramic view in mind. And while operators are trained to manoeuvre with caution, blind spots are still causing far too many “I didn’t see it” moments on the jobs.

→ Reality Check: The Risks are Real 

• People are paying the price, literally and physically: Approximately, 25% of forklift-related accidents involve pedestrians, with blind spots contributing 55% of these incidents.

• Increased risks during reverse operations: Shockingly, near about 70% of forklift-related fatalities involve pedestrians being struck while the forklift is reversing, highlighting the dangers of rear blind spots.

• Fatalities due to limited visibility: In the U.S., there are close to 100 forklift-related deaths each year, with a significant portion resulting from operators’ limited visibility.

→ Economic Implications

Forklift blind spot is not just a safety issue; it is a financial drain too:

• Forklift-related injuries typically incur approximately $50,000, including medical bills, legal expenses, and productivity losses.

• Beyond the human toll, forklift accidents can also lead to operational delays, equipment damage, and increased premiums.

The risks of forklift blind spots extend beyond pedestrians to include operators, inventory, and facility infrastructure. And as loads get bigger, and workflows get busier, these unseen zones become harder to manage without real-time support.

If forklift blind spots are the stealthy threats of warehouse safety, video analytics is the powerful solution. More than just smart surveillance, video analytics combines the brainpower of AI CCTV, the precision of computer vision and the clarity of IP cameras – all to ensure that what operators can’t see, no longer puts safety at risk.

Here’s how video analytics steps in to tackle forklift blind spots head-on:

1. Forklift Blind Spot Monitoring: Video analytics continuously scans live feeds from IP cameras mounted on the forklifts. Using computer vision, it detects motion, people and objects in real-time, especially in areas hidden from the operator’s line of sight. This kind of forklift blind spot monitoring enhances operational visibility and reduces the chances of unnoticed hazards, giving operators an extra set of eyes that never blinks.

2. Real-time Object & Human Detection: Video analytics uses computer vision to instantly detect pedestrians, vehicles, or obstacles in the forklift blind spots. Unlike traditional mirrors or alarms, it provides real-time identification and tracking through live feeds from the IP cameras, significantly improving response time and situational awareness.

3. Forklift-Pedestrian Interaction Monitoring: Video analytics helps track proximity between forklifts and pedestrians, even in fast-paced environments. By detecting path intersections in real-time using computer vision, it can trigger both – the forklift and pedestrian – and also notify supervisors before a near-miss becomes a reportable incident. 

4. Multi-angle Forklift Blind Spot Coverage: The mounted IP camera(s) around the forklift feed into a central video analytics engine that monitors zones typically hidden from view. This ensures consistent visibility across all critical angles without relying solely on driver perception.

5. Zone-based Danger Mapping: Video analytics can be configured to create geo-fenced danger zones around specific blind spot areas, like loading docks or crossing points. Using AI CCTV and IP cameras, the system monitors these zones and flags violations, such as unauthorized personnel entry, before the forklift even gets close.

6. Behavioural Safety Monitoring: Through continuous analysis of driving patterns, video analytics can flag risky behaviours such as sudden acceleration, near blind corners, aggressive reversing, or failure to slow down at intersections. These insights can be used to train drivers and improve forklift handling practices.

7. Night-time & Low-Light Monitoring: With the support from IP cameras equipped with low-light capabilities, AI video analytics ensures forklift blind spot safety isn’t compromised by dark. This is especially critical for 24/7 industrial operations or dimly lit warehouse zones.

8. Real-time Emergency Alerts: With AI CCTV and video analytics, it is no longer about noticing danger, it is about being warned before it strikes. The system identifies risky proximity scenarios, like a person walking into a rear blind spot, and triggers audible or visual alerts to prevent accidents, especially during turning or reversing.

Thus, video analytics acts like a co-pilot, not a distraction. With minimal interface clutter, the system works quietly in the background, processing feeds from AI CCTV and IP cameras, and only intervening when something is actually wrong.

Safer driving without information overload.         

The fisheye mirror reflects shapes. A sensor beeps if something gets too close. But neither knows what is really going on. Video analytics, on the other hand, gives forklifts a second opinion – one backed by algorithms, not guesswork.

A forklift turns a blind corner in a crowded warehouse. A convex mirror mounted high up gives a blurry view – just enough to see movement, but not enough to know what’s there. The operator slows down, but it’s already too late. A pallet jack operator was in the exact spot.

Now replay the moment with video analytics:

As the forklift approaches the corner, AI CCTV and IP cameras stream live data into a computer vision engine. It doesn’t just “see”, it “identifies”. The system flags the moving pallet jack, flashes a visual cue to the driver, and sounds an alert in both zones. Collision? Prevented.

Traditional tools rely on hope, human reaction, and limited perspectives. Video analytics doesn’t wait for accidents to happen; it predicts, detects, and prevents them in real-time. It is an ever-watchful guardian that adapts to every angle, every environment, and every shift – day or night.

In fast-paced, low-visibility settings, traditional safety measures are like trying to find your way through a fog. Video analytics provides crystal-clear visibility, helping operators navigate safely and effectively through forklift blind spots.

A split-second of uncertainty can cause a long-lasting consequence. Every blocked angle, every obstructed path adds friction to an already high-stakes environment. While traditional tools may warn, they rarely intervene. A beeping alarm doesn’t tell you what the threat is. A mirror can’t say how close it’s getting. And human intuition, no matter how trained, was never meant to work in isolation against fast-paced machines and unpredictable surroundings.

Here, video analytics flips the dynamic, stepping in before doubt becomes danger. By transforming raw camera footage into contextual insights, systems like viAct don’t just enhance operator awareness, they extend it. Whether it is flagging a pedestrian in the rear zone, tracking risky turns, or monitoring behavioural patterns over time, video analytics gives forklifts a set of eyes that don’t blink and a brain that doesn’t guess. In the world of modern industrial safety, this is not a luxury; it is a necessity. Because the next near-miss should never become the next accident, and with the right tech, it doesn’t have to.

Forklift blind spots are areas around the vehicle that the operator cannot see clearly, often due to mast structures, bulky loads, or tight aisle layouts. These blind zones increase the risk of collisions with pedestrians, equipment, or infrastructure.

Tighter warehouse layouts, higher racking systems, larger forklift sizes, and faster-paced operations all amplify the danger of blind spots, making traditional mirrors or spotters insufficient without tech intervention.

While AI can’t physically remove blind spots, it can detect potential hazards in those zones in real-time using AI-enabled CCTV and Computer Vision, drastically improving operator awareness and reducing incidents.

Video analytics analyze live video feeds to detect objects, people, or unsafe behaviours in proximity to forklifts. They trigger real-time alerts for operators or supervisors, helping avoid collisions and unsafe manoeuvres.

Facilities like warehouses, manufacturing plants, and logistics hubs, especially those with high forklift traffic and limited visibility, see the greatest benefits of using video analytics for forklift blind spot safety. It is particularly valuable in areas where frequent human-pedestrian interaction heightens safety risks.

Worried about forklift blind spots putting your workforce at risk?