Forklifts no longer operate in isolation. On today’s warehouse and distribution floors, they’re increasingly sharing space with automated guided vehicles (AGVs), autonomous mobile robots (AMRs), and pedestrians, and the safety and fleet management technology built around them is converging to keep pace. To understand what that shift looks like on the ground, we sat down with Alex Johns, president of ELOKON North America.
ELOKON has spent more than 40 years developing safety, driver-assistance, and fleet management technology for forklifts and other material handling equipment, and today serves more than 4250 customers worldwide. Johns shared his perspective on where the industry is headed, how customer priorities are changing, and what it takes to keep people, forklifts, and autonomous vehicles working side by side safely.
FR: Tell us about ELOKON and where you fit in the material handling market.
AJ: ELOKON is an OEM-independent provider of automated safety, driver-assistance and fleet management systems for forklifts and other material handling equipment. Our technologies help customers improve safety, productivity and visibility as operations become more connected and automated. The OEM independence matters in mixed-fleet environments, since customers aren’t tied to one vehicle manufacturer.
Our focus has grown from forklift safety into a broader challenge: helping humans, conventional equipment and autonomous vehicles operate safely together. That includes forklifts, AGVs and AMRs.
FR: What are the major industry trends you’re seeing?
AJ: The material handling sector is shifting from siloed technologies toward unified, autonomous, data-driven systems.
One key shift is sensor fusion, which combines data from ultra-wideband (UWB), AI-driven cameras, RFID, telematics and other sensing technologies. Cross-verifying multiple sources helps systems confirm whether a real risk exists, moving from basic warnings toward safety-rated systems that can automatically slow or stop a vehicle.
The use of AGVs and AMRs also continues to grow, creating a need to manage mixed fleets. About 85% of U.S. facilities already run mixed fleets, so operators need visibility across multiple forklift brands and autonomous equipment.
The larger trend is convergence: safety, fleet management, location intelligence, automation and AI are no longer separate technologies. Customers want them working together.
FR: How are customer priorities shifting?
AJ: The top priority we’re seeing is simplicity. Customers are tired of what we call the “integration nightmare,” where they’re managing multiple, different software systems for fleet management, warehouse management and safety. They want to consolidate vendors, simplify deployment and have one source of truth for their operation. They don’t want another proprietary system creating another data silo; they want one interoperable system that works across vehicle types and OEMs.
Customers don’t necessarily want identical setups at every facility either. They want technology that scales to each site’s risk level and operational needs.
For example, one executive we spoke with oversees a campus of four facilities and roughly 500 material handling vehicles. Two buildings had dense workflows that needed active proximity detection, while the other two had good pedestrian-equipment separation and mainly needed fleet management. We could support both cases while keeping a single platform and dashboard across the enterprise, so companies can invest where it adds the most value without creating a fragmented system.
Mixed fleets also raise real safety challenges. One example: manual forklifts and low-profile AGVs or AMRs. Autonomous vehicles have onboard sensors, but their low profile can be hard for a forklift operator to see — and their sensors may not recognize the raised mast of a conventional forklift. The latest technologies bridge that gap by normalizing the data, treating an approaching AGV or AMR the same as an approaching pedestrian. The forklift operator gets consistent proximity information regardless of whether the hazard is a person or a machine.
FR: Does proximity detection identify the parties involved, and can that data support safety training?
AJ: Yes. Promimity detection technologies can capture and report who or what was involved in a proximity event. This is especially valuable for Environment, Health and Safety (EH&S) managers. Most facilities already have solid baseline safety protocols, including barriers, walkways, and fencing, but pedestrians and equipment still interact in complex environments.
Our technology can show how often equipment enters high-risk zones, letting managers spot vulnerabilities, recognize strong compliance and turn near-misses into useful insights.
Instead of just recording incidents after they happen, managers can spot traffic patterns, target retraining and address risky behavior before it causes an accident. This shifts safety from reactive to proactive.
FR: How do you see automation changing the relationship between people, forklifts and other material handling equipment?
AJ: As automation grows, pedestrian detection and human-machine interaction matter more.
A single facility may have manual forklifts, AGVs, AMRs and pedestrians all sharing the same space. The goal is to make those interactions safe without adding excessive infrastructure or complexity.
The right technology can automatically slow, stop or reroute a vehicle when it detects real risk. This protects people as well as expensive autonomous equipment and reduces operational disruption.
The economics matter too. Autonomous equipment damaged by conventional forklifts can be costly, so preventing those incidents is typically both a safety and a business priority for most companies.
FR: How does this all work if a facility has a mixed fleet of forklifts as well as autonomous vehicles like AMRs and AGVs?
AJ: Most facilities operate with mixed fleets of manual forklifts, AGVs and AMRs operating together. One of our largest North American customers, a major automotive manufacturer, runs an environment with constant close-quarters interaction among pedestrians, AGVs, AMRs and conventional forklifts.
The challenge is that autonomous-vehicle safety systems and manual forklift operators aren’t necessarily designed with each other in mind. We bring these different assets into a common safety framework.
Our roadmap also includes broader AGV/AMR integration and support for interoperability standards such as VDA 5050, so autonomous fleets can be managed as part of one unified ecosystem.
FR: Where do you see sensing technology going next?
AJ: The next major step is advanced sensor fusion. We already use stationary infrastructure sensors for fixed high-risk areas such as blind intersections, loading docks, and narrow corridors. But we’re also working to reduce dependence on fixed infrastructure.
By combining UWB, AI vision and infrastructure-free real-time location technology, forklifts can increasingly determine their own position using onboard sensing and environmental references. That opens the door to accurate digital twins of facilities without the cost and complexity of traditional RTLS infrastructure.
The next breakthrough is making that data useful. Facilities already generate huge amounts of information from fleet management and proximity detection. The real challenge for EH&S and operations managers is making that data digestible, not gathering more of it. That’s where AI and large language models (LLMs) can help.
FR: How do you expect AI to be used in material handling?
AJ: We expect AI to move from a theoretical concept to a practical tool for interpreting data and improving safety. A facility manager shouldn’t need to be a data scientist to answer a question like “Who was my most productive driver last week?” An AI-enabled system can interpret the underlying fleet data and turn it into a clear answer.
The same technology can spot behavioral trends, predict bottlenecks and flag developing safety risks.
AI will also play a bigger role in sensor fusion. For example, AI vision can help confirm whether an object is a person, while UWB provides precise distance. Combining these reduces false alarms and ensures interventions happen only when there’s a genuine, verified risk. The goal isn’t AI for its own sake. It’s turning huge amounts of operational data into information people can actually use to make faster, better decisions.
FR: How are safety standards and regulations different in Europe than in the United States?
AJ: Europe and the U.S. differ significantly here. In Europe, safety requirements are often tied to specific vehicle types. VNA trucks operating in controlled aisles, for example, have long been subject to certified safety-system requirements.
The U.S. market is different, largely because mixed fleets are so common. OEMs offer strong proprietary safety systems, but operators increasingly need one solution that works across multiple forklift brands. Safety shouldn’t depend on a specific OEM — it needs to be fleet-agnostic and able to evolve as a facility’s equipment mix changes.
The U.S. also relies heavily on OSHA guidelines rather than equipment-specific mandates. Fleet management data already plays a role in showing that required inspections and safety processes have been completed.
We believe the U.S. will eventually set a baseline expectation for active proximity detection on forklifts. Passive technologies like projected warning lights still have value, but they’re not enough for increasingly complex environments where pedestrians, forklifts, AGVs and AMRs all interact. As those interactions grow, the case for standardized active proximity detection will become harder to ignore.
AJ: What’s your outlook for the industry?
Demand for these technologies is real. Customers aren’t just interested in new technology for its own sake — they’re actively looking for ways to make facilities safer and more efficient while simplifying the systems they manage.
We don’t see that momentum slowing down, and we don’t see the technology or the industry slowing down either.
