Every year, thousands of warehouse workers experience injuries on the job—and some of the most severe are caused by being caught in or crushed by machinery. In fact, forklift accidents alone account for approximately 95,000 injuries in U.S. warehouses each year (Source: OSHA, 2025). But here’s the good news: most of these injuries are preventable. When organizations combine proven safety protocols with technology like AI-powered video analytics, they move from reacting after an incident to proactively stopping the next one before it happens. 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 Caught-in or Crushed by Machinery Accidents Are So Costly in Warehousing
Caught-in or crushed by machinery incidents are among the most disruptive and expensive safety challenges in warehousing. These events often involve powered industrial vehicles, conveyors, and heavy objects—equipment found in every busy warehouse.
The numbers tell the story:
5% of warehouse workers experience injuries each year, with 3.7 serious cases per 100 workers (Source: BLS, 2025).
Forklift-related incidents remain the most hazardous, averaging $38,000–$41,000 per claim and contributing to a total industry injury cost of $5.8 billion annually (Source: OSHA, 2025; Innovative Human Capital, 2025).
Conveyor systems account for 25% of workers’ comp claims—often involving crush injuries and amputations (Source: IEN, 2025).
But the impact isn’t just about claims and medical bills. Every caught-in or crushed-by incident can trigger cascading indirect costs: downtime, rerouting workflows, lost productivity, and increased insurance premiums. In some cases, the total cost of a single serious accident can exceed $200,000 once all factors are included.
And beyond the financials, these events erode trust, disrupt teams, and can put an organization’s OSHA compliance record—and reputation—at risk.
The Top 5 Causes of Caught-in or Crushed by Machinery Accidents in Warehousing—and How to Prevent Them
Understanding the real-world causes behind these incidents is the first step to stopping them. Let’s break down the five leading causes, how traditional prevention works, and how AI video intelligence can supercharge your safety program.
1. Unsafe Operation of Powered Industrial Vehicles
The Hazard:
In one scenario, a warehouse associate steps off a stand-up forklift before it comes to a complete stop, intending to reposition a load. The forklift continues to roll, pinning the worker’s foot between the vehicle and a storage rack. These situations are common when operators or pedestrians let their guard down around moving equipment.
Traditional Prevention:
OSHA-mandated operator training and certifications.
Strict enforcement of seat belt and body restraint policies.
Visual and audible alerts (horns, alarms) in high-traffic zones.
Marked pedestrian walkways and exclusion zones.
How AI Amplifies Prevention:
AI-driven video analytics can detect when a forklift enters a no-go zone, approaches a pedestrian, or when a near-miss occurs. Real-time alerts let supervisors intervene before a close call turns into an incident. By automatically flagging risky vehicle-pedestrian interactions, safety leaders get the data they need to adjust workflows, retrain staff, and reinforce protocols—without waiting for an incident report (Source: Spot.ai Capabilities).
2. Failure to Lock Out/Tag Out (LOTO) During Maintenance
The Hazard:
A maintenance technician removes the guard on a live conveyor belt for a quick fix, thinking “it’ll only take a minute.” As they reach into the moving mechanism, their glove is caught by the chain drive, resulting in a finger amputation. Incidents like this are frequently traced to skipped LOTO procedures.
Traditional Prevention:
Written LOTO procedures and mandatory training.
Regular audits of LOTO compliance, especially during shift changes.
Supervisor sign-off before equipment is serviced.
How AI Amplifies Prevention:
AI video analytics can monitor for missing personal protective equipment, detect when guards are removed, and flag unauthorized access to restricted or dangerous zones. With real-time alerts, EHS teams are notified instantly when LOTO protocols—or other safety measures—are bypassed. Event footage provides a clear record for investigation, root cause analysis, and retraining (Source: Spot.ai Capabilities).
3. Inadequate Machine Guarding
The Hazard:
During a busy shift, a worker notices that the guard on a conveyor’s pinch point is missing but continues operating the machine to keep up with demand. Later, while clearing a minor jam, their hand is caught between the moving belt and roller. Lack of guarding remains one of the leading contributors to crush and amputation injuries.
Traditional Prevention:
Routine inspections for missing or damaged guards.
Signage and physical barriers highlighting dangerous zones.
Disciplinary policies for bypassing or removing guards.
How AI Amplifies Prevention:
AI-powered systems can continuously monitor for people entering no-go zones or loitering near hazardous equipment. When someone is detected in a restricted area, or a guard is visibly absent, supervisors are alerted in real time. This proactive approach helps prevent unsafe shortcuts and maintains high standards for guarding—even during peak periods (Source: Spot.ai Capabilities).
4. Unsafe Manual Handling of Heavy Objects
The Hazard:
A loader attempts to reposition a heavy dock plate by hand instead of using a mechanical assist. Their hand slips, and the plate drops, crushing their fingers between metal surfaces. Manual object handling near heavy equipment often leads to hand, finger, and foot injuries.
Traditional Prevention:
Training on proper lifting techniques and team lifts.
Use of mechanical aids (hoists, lift assists) for heavy items.
PPE requirements such as steel-toed boots and gloves.
How AI Amplifies Prevention:
Video analytics can spot missing PPE, detect when people are present in unsafe areas, and flag loitering or crowding near heavy equipment. By surfacing these patterns, safety leaders can address risky behaviors before they result in injury, reinforce the use of mechanical aids, and ensure that PPE policies are followed (Source: Spot.ai Capabilities).
5. Poor Traffic Management and Pedestrian Safety
The Hazard:
A picker moves quickly between aisles to keep up with orders, unaware that a forklift is turning into the same aisle. Without clear line-of-sight, the two collide, pinning the worker’s leg. Crowded warehouses, unclear walkways, and uncoordinated vehicle movement increase the risk of these incidents.
Traditional Prevention:
Marked pedestrian zones and crossing points.
Traffic flow planning and designated travel routes.
Pedestrian awareness training and mirrors at blind spots.
How AI Amplifies Prevention:
AI video systems identify people and vehicles entering no-go zones, track crowding in high-traffic areas, and signal when forklifts are operating outside designated paths. Automated incident detection means safety teams can analyze near-misses, adjust routes, and optimize schedules—making real, data-driven improvements to warehouse layouts and workflows (Source: Spot.ai Capabilities).
Integrating a Modern AI Camera System: From NVR to AI Insights in Warehousing
Many warehouse operations already have some form of CCTV or NVR (Network Video Recorder), but these traditional systems are reactive—they only provide footage after something’s gone wrong. Upgrading to an AI-powered video platform moves safety from a passive cost center to a proactive engine for compliance and operational excellence.
How It Works:
Seamless Integration: Modern AI camera systems are designed to work with your existing infrastructure—including common Power over Ethernet (PoE) cameras. No need for expensive “rip-and-replace” projects.
Cloud-Native Storage: By bridging your on-prem cameras to a secure, cloud-native dashboard, you eliminate bulky on-site servers and get scalable, reliable video storage.
AI Analysis Layer: The real differentiator is the AI layer that sits atop your video feeds. Instead of endless manual review, AI surfaces critical events—such as forklift near-misses, people in no-go zones, or missing PPE—in real time.
Unlimited User Access: With a unified dashboard and unlimited user seats, safety, operations, and IT teams can collaborate seamlessly, breaking down silos.
Scalable and Low Maintenance: Remote updates and centralized management reduce IT burden. Adding new cameras or locations becomes as simple as plug-and-play.
Here’s how it compares at a glance:
Feature | Traditional NVR System | Modern AI Video Platform |
|---|---|---|
Camera Compatibility | Often requires new hardware | Works with existing PoE cameras |
Storage | On-premise, limited | Secure, cloud-native, scalable |
Maintenance | Frequent, on-site | Minimal, remote updates |
User Access | Limited, siloed | Unlimited users, unified dashboard |
Video Review | Manual, slow | AI-powered search & detection |
Actionable Insights | Passive footage | Real-time alerts & analytics |
A cloud-based AI solution helps warehouse teams reduce incident investigation time by up to 95%, enforce OSHA compliance, and create a safer, more accountable workplace.
Practical Tips for Warehousing Leaders
Evaluate Your Current Camera Coverage: Identify high-risk zones—forklift aisles, dock areas, conveyor lines—and ensure they are in view.
Prioritize AI Capabilities: Look for platforms that detect forklift near-misses, PPE compliance, and restricted area breaches.
Plan for Collaboration: Choose solutions that offer unlimited user access so safety, ops, and IT can work together.
Integrate with Safety Protocols: Use AI video data to support incident investigations, training, and continuous improvement cycles.
Transform Your Warehouse Safety—Book a Safety Consultation
Every caught-in or crushed-by machinery incident is a call to do better—not just to react, but to get ahead of the next risk. By integrating robust AI-driven video analytics with your existing safety protocols, you can prevent injuries, streamline investigations, and build a culture of safety that lasts.
Ready to see how AI video analytics can empower your warehouse safety program? Book a safety consultation with Spot AI’s experts to get tailored, actionable guidance for your operation.
Frequently asked questions
What are the most common causes of caught-in or crushed by machinery injuries in warehousing?
The top causes include unsafe operation of forklifts and pallet jacks, failure to follow lockout/tagout procedures during maintenance, inadequate machine guarding, unsafe manual handling of heavy objects, and poor traffic management in high-density areas (Source: OSHA, 2025).
How can modern safety technology be implemented in an existing warehouse without replacing all cameras?
Modern AI video platforms are designed to work with your current camera infrastructure, including standard PoE cameras. They overlay analytics on your existing feeds, so you can upgrade to proactive safety monitoring without a complete hardware overhaul.
What are best practices for integrating AI video analytics into a warehouse safety program?
Start with a risk assessment to identify high-priority areas. Engage both IT and safety teams early in the process. Choose a platform that offers real-time alerts, unlimited user seats, and open APIs for integration with your incident management systems.
How does AI video help with OSHA compliance?
AI video analytics support OSHA compliance by continuously monitoring for key violations—like forklifts in pedestrian zones, missing PPE, or LOTO bypasses. Automated alerts and searchable video archives make it easy to investigate incidents and document compliance actions (Source: OSHA, 2025).
What training is needed for teams to use AI video analytics effectively?
Most frontline teams can use cloud-based AI video dashboards with minimal training. It’s best practice to run onboarding sessions for safety leaders and supervisors, focusing on incident review workflows and how to respond to real-time alerts.
How can safety technology help reduce stress for warehouse safety managers?
AI-powered analytics automate hazard detection and reporting, freeing safety managers from tedious video review and manual monitoring. This lets them focus on coaching, process improvement, and building a strong safety culture.
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.
