How ArrowSpot Is Enabling Reefer Logistics to Move from Failure Detection to Cargo Assurance

ArrowSpot’s AI-driven intervention and analytics are enabling logistics providers to resolve failures in real time – and prevent recurring risks across the logistics network

By: Yoav Mimran

Detection Is Not the Problem. Resolution Is.

Today, refrigerated cargo loss is no longer a visibility problem. Across most modern fleets, telematics and monitoring systems already transmit temperature deviations, power loss and controller alerts in real time. The data is there – the issue is what happens next.

By the time alerts are reviewed, escalated and acted upon, valuable cargo may already be exposed to hours of temperature risk. Manual triage processes, fragmented communication chains and delayed technical response continue to drive cargo loss -along with insurance claims, SLA penalties and customer dissatisfaction – even when the underlying failure was detected early.

Two recent incidents illustrate what becomes possible when ArrowSpot’s AI-driven intervention and network-level analytics are applied in practice.

Reefer Container Loaded on a Train During Intermodal Transit

Case 1: AI-Driven Intervention Saved Cargo at Rail Terminal

A reefer container carrying raw materials for chocolate production was en route from the United States to Brazil when ArrowSpot’s AI-powered monitoring system flagged a critical issue: the unit had been powered off while still staged at Chicago’s rail terminal, and the temperature inside was already declining – placing its cargo at imminent risk.

Cross-referencing the train’s departure schedule, the container’s precise location on the railcar, and the power status of neighbouring units, ArrowSpot’s AI system determined that this container should already have been connected to power, that others on the same railcar had been running for several hours, and that the train was due to depart shortly. Immediate action was flagged as essential.

Acting on the system’s alert and precise location intelligence, the intervention team contacted terminal services and escalated for on-site inspection before departure. Initial feedback indicated the unit would only be checked on arrival at Port Newark.

The AI-generated evidence – pinpointing the container’s exact position and confirming the urgency of the time window – made the case impossible to dismiss.

Thanks to ArrowSpot’s intervention, the container was de-ramped, inspected and restored to operating temperature before the train left Chicago. The shipment continued its journey fully intact, with zero cargo loss.

Technicians Performing Reefer Maintenance

Case 2: Catching “Invisible” Systemic Power Failure at Port

Real-time intervention is only one part of the challenge. Across ports, vessels and depots, recurring infrastructure constraints often remain invisible at the network level – allowing the same avoidable risks to repeat voyage after voyage.

ArrowSpot’s AI-powered network-level analytics recently identified a critical reefer power failure during discharge operations at the Port of Veracruz. The numbers were stark:

Key Findings — Port of Veracruz

121 reefer containers discharged

4.5 hrs average power-off duration per unit

45 reefers exceeded 6 hours without power

322 power-off alarms triggered (exceeding 2 hours)

35 reefers simultaneously disconnected for 3+ hours during real-time monitoring (avg. 4.2 hrs)

No equipment had malfunctioned. Analysing the pattern of alarms across all 121 units, ArrowSpot’s AI-powered system identified insufficient electrical capacity at the terminal as the root cause – flagging the repeated connect/disconnect cycles as a port infrastructure failure rather than an equipment fault. Every one of those cycles meant hours of temperature exposure for cargo requiring continuous refrigeration.

Without network-level analytics, this type of infrastructure constraint typically goes undetected until cargo quality complaints or insurance claims are filed – by which point the vessel has called again and the same failure has repeated.

In this case, ArrowSpot enabled the pattern to be identified before the next vessel call. Generator allocation and power planning were adjusted proactively, significantly reducing power-off events on subsequent operations at the same terminal.

24/7 Control Center

Managing Cargo Reliability as a Service Outcome

These cases reflect a broader shift underway in reefer logistics, moving from reacting to individual failures toward identifying and addressing the conditions that cause them.

To reduce cargo loss and commercial exposure, logistics providers need two complementary capabilities: the ability to prevent cargo damage before it occurs – rather than manage the consequences following an incident – and the ability to detect infrastructure and operational weaknesses across the network before they cause repeated harm.

ArrowSpot addresses both through two integrated solutions:

ArroWatch 24/7 provides proactive in-transit intervention for high-value cargo incidents – predicting faults and surfacing potential failure points before they occur, filtering, classifying and prioritising alerts using AI-supported decision tools, and coordinating on-ground technical response teams when time-critical action is required.
ArrowDesk Analytics detects failure patterns across the entire cold chain – ports, depots, rail terminals and beyond. By analyzing recurring technical faults in refrigeration units alongside how response teams worldwide handle and resolve them, it gives logistics managers the visibility to identify systemic risks before they translate into cargo damage or commercial disruption.

As cargo values increase and refrigerated supply chains grow more complex, the ability to prevent cargo damage – rather than address it after the fact – is becoming a genuine commercial differentiator.

Both outcomes were made possible by ArrowSpot’s AI platform – purpose-built to give logistics providers the intervention speed and network intelligence needed to manage cargo reliability as a guaranteed service outcome across ports, vessels and intermodal transport environments.

About ArrowSpot

ArrowSpot delivers AI-powered cargo monitoring and real-time intervention for refrigerated cargo across the global supply chain. Where traditional monitoring systems report problems, ArrowSpot’s platform enables shipping lines and logistics providers to actively manage reliability – intervening before equipment failures become cargo damage or commercial loss.

ArrowSpot Systems Ltd

Website: www.arrowspot.com