Each year, struck-by moving objects accidents rank among the most serious—and expensive—workplace injuries in warehousing. In 2023 alone, U.S. retail and warehousing employers faced $5.8 billion in injury-related losses, with struck-by object or equipment incidents consistently among the top drivers of these costs (Source: Liberty Mutual, 2025; Source: Innovative Human Capital, 2025). These injuries disrupt operations and drive up insurance costs.
But here’s the good news: most struck-by accidents are preventable. By combining proven safety protocols with modern AI-powered video analytics, safety leaders can move from reacting after an incident to preventing them in real time. This guide breaks down the true costs, root causes, and provides a clear framework for moving from a reactive to a proactive safety model using modern technology.
Why Struck-by Moving Object Accidents Are a Major Liability for Warehousing
Struck-by accidents are more than just a safety statistic—they are a leading operational risk for any warehouse. Unlike minor bumps or cuts, these incidents often involve heavy machinery, falling objects, or vehicle collisions, resulting in severe injuries to feet, legs, hands, and hips.
The average OSHA penalty per incident is $8,955, but that’s just the tip of the iceberg. Indirect costs—like overtime, temporary staffing, retraining, lost productivity, and legal fees—can multiply the total impact by three to five times the direct expense. In a high-turnover, fast-moving environment, even a single incident can disrupt schedules and delay shipments.
Struck-by incidents are a top driver of lost-time injuries, regulatory fines, and operational headaches in warehousing. Proactive prevention isn’t just best practice—it’s mission-critical for financial and operational health.
The Top 5 Causes of Struck-by Moving Objects Accidents in Warehousing—and How to Prevent Them
Understanding why these accidents happen is the first step. Here are the top five causes in warehouses, with actionable prevention strategies and how AI video analytics can supercharge safety efforts.
1. Forklift and Vehicle Collisions
The Hazard:
In a bustling distribution center, a worker heads down an aisle just as a forklift operator—carrying a high stack—turns the corner. The load blocks the operator’s view. There’s no physical barrier, and the two collide. Incidents like this are frequent, especially at intersections or when visibility is low.
Traditional Prevention:
Traffic management plans with painted walkways and designated crossing points.
Physical barriers and bollards to separate people and machines.
Operator certification and refresher training.
Speed limits and right-of-way rules.
How AI Amplifies Prevention:
AI-powered video analytics can monitor intersections and high-traffic aisles 24/7. The system can detect “forklift near miss” events and “vehicle enters no-go zones,” flagging unsafe interactions between vehicles and pedestrians in real time. Safety teams get instant alerts and can review incident clips, making it easy to identify problem areas and retrain staff before an accident occurs.
2. Falling Objects from Racks or Loads
The Hazard:
A worker is picking orders below a high rack when a poorly stacked pallet above shifts and drops several boxes. Injuries to the head, neck, and shoulders are common; in some cases, workers are struck in the legs or feet by heavy items.
Traditional Prevention:
Regular inspection of pallet racks for overloading and damage.
Use of load securing (wrapping, strapping).
Rules for safe stacking heights and weight limits.
PPE enforcement—hard hats and safety footwear.
How AI Amplifies Prevention:
AI video analytics can monitor racks and storage zones for unsafe stacking, loitering in danger zones, or “possible fall” events involving objects. When a worker enters a no-go zone under a raised load, the system can alert supervisors instantly, helping enforce best practices and trigger fast interventions.
3. Unsafe Maintenance and Clearing Jams
The Hazard:
During a busy shift, a worker tries to clear a jam in a conveyor without shutting it down. The conveyor starts moving, and the worker’s hand is caught between moving parts. Many injuries—especially amputations—happen when safety procedures are skipped for the sake of speed.
Traditional Prevention:
Lockout/tagout (LOTO) protocols for all maintenance.
Machine guarding and regular equipment checks.
Task-specific training and refresher courses.
Incident reporting and root cause analysis.
How AI Amplifies Prevention:
AI systems can detect when a person is present in a restricted area (“person enters no-go zones”) or when machine guards are removed, sending alerts to supervisors. Reviewing flagged video clips enables safety teams to pinpoint unsafe practices and reinforce LOTO compliance.
4. Loading Dock and Door Accidents
The Hazard:
A worker is unloading a truck at a loading dock. Wind catches an unsecured door, or a semi-truck moves unexpectedly—striking workers or causing loads to fall. Many incidents involve doors, dock plates, and miscommunication between drivers and warehouse staff.
Traditional Prevention:
Use of dock locks and wheel chocks to secure trailers.
Clear communication protocols between drivers and staff.
Regular inspection and maintenance of dock equipment and doors.
Signage and floor markings to keep people out of danger zones.
How AI Amplifies Prevention:
AI analytics can monitor loading docks for “vehicle enters no-go zones,” flagging unsafe vehicle movement or pedestrians in restricted areas. Real-time alerts help prevent dock strikes, and recorded footage streamlines incident investigations.
5. Poor Visibility and Environmental Factors
The Hazard:
A worker rounds a corner in a dimly lit aisle, unaware a forklift is approaching in reverse. Obstructed sightlines, wet floors, and cluttered walkways can all contribute to struck-by injuries.
Traditional Prevention:
Adequate lighting and regular housekeeping.
High-visibility PPE for workers.
Mirrors at intersections and blind spots.
Environmental controls (anti-slip flooring, ventilation).
How AI Amplifies Prevention:
AI-powered cameras can flag “running” (a sign of rushing or distraction), “loitering” in unsafe areas, or “crowding” in aisles. By highlighting near-miss patterns in specific spots, safety teams can target lighting upgrades or adjust floor layouts for better visibility and flow.
Integrating a Modern AI Camera System: From NVR to AI Insights in Warehousing
For Operations, Safety/EHS, or IT managers, upgrading safety tech usually sparks concerns: Will it work with our existing cameras? Will we need to rip out all our hardware? What about storage and user access?
Here’s how a modern AI camera system fits into your warehousing environment:
Feature | Traditional NVR System | Modern AI Camera Platform |
|---|---|---|
Camera Compatibility | Often requires new cams | Works with existing POE/legacy cams |
Storage | On-premise hardware | Secure, cloud-native, scalable |
Maintenance | Frequent, on-site | Minimal, remote updates |
User Access | Limited seats | Unlimited users, unified dashboard |
Video Review | Manual, slow | AI-powered search & incident detection |
Actionable Insights | Passive footage | Real-time alerts for near misses, no-go zone violations, and more |
A cloud-based AI solution bridges your existing cameras—old or new—to a secure, cloud-native dashboard. No need to rip and replace. It automates detection of critical safety events (like forklift near misses or no-go zone entries), flags footage for fast review, and empowers unlimited users to monitor and act—all from a single dashboard.
Unlike standard NVRs, the AI layer transforms video from a passive record into an active safety tool. It surfaces actionable insights: near-misses, no-go zone violations, running, crowding, and more—so your team can respond before a minor issue becomes a major incident.
Practical integration tips:
Prioritize solutions that support your current OSHA compliance and traffic control policies.
Look for platforms that accept both modern and legacy camera feeds.
Choose systems with real-time insights and unlimited user access, so safety isn’t siloed.
Align technology upgrades with broader safety goals—integrate with training, incident reporting, and regular risk audits.
Transform Warehouse Safety—Book a Safety Consultation
Every struck-by incident is a signal—an opportunity to build safer habits, stronger teams, and more resilient operations. With the right combination of proactive protocols and AI-powered video analytics, warehousing leaders can dramatically cut accidents, speed up investigations, and make sure every worker goes home safe.
Ready to see how modern video intelligence can empower your safety team and prevent the next costly accident? Book a safety consultation with Spot AI’s experts to get actionable, tailored guidance for your operations.
Frequently asked questions
What are the main causes of struck-by moving objects injuries in warehousing?
The leading causes are collisions with moving vehicles (especially forklifts and pallet jacks), being struck by falling objects, caught hands or feet in equipment, doors or dock plates striking workers, and poor visibility in aisles (Source: OSHA Data, 2025).
How do I prevent forklift and vehicle collisions in my warehouse?
Combine strict traffic management (barriers, floor markings), regular operator and pedestrian training, and ongoing equipment maintenance. AI video analytics can detect near-misses and no-go zone violations in real time, helping you address risks before they become injuries.
Can AI camera systems work with my existing warehouse cameras?
Yes. Modern cloud-based AI camera platforms are designed to work with most existing POE or legacy cameras. They add an AI analysis layer on top of your current video feeds, so you don’t need to replace your entire camera network.
What practical steps should I take before deploying safety technology in my warehouse?
Start with a risk assessment—identify high-traffic and high-risk zones, review camera coverage, and engage your safety, operations, and IT teams. Pilot the AI system in a problem area, review the alerts and insights, and expand based on measurable improvements.
How can safety technology help reduce stress for warehouse safety managers?
AI-driven analytics automate hazard detection, freeing safety managers from endless manual monitoring and paperwork. This lets them focus on proactive planning and team engagement, rather than reacting to every incident.
Does using AI video analytics help with OSHA compliance?
Absolutely. AI video analytics support compliance by automatically flagging safety violations, providing searchable incident records, and giving you data-driven insights to improve training, policies, and audits (Source: OSHA Data, 2025).
About the author
Joshua Foster
IT Systems Engineer, Spot AI
Joshua Foster is an IT Systems Engineer at Spot AI, where he focuses on designing and securing scalable enterprise networks, managing cloud-integrated infrastructure, and automating system workflows to enhance operational efficiency. He is passionate about cross-functional collaboration and takes pride in delivering robust technical solutions that empower both the Spot AI team and its customers.
