Every year, about 30–40% of food is wasted in the U.S., worth $161 billion most of it at the retail and consumer levels.
Additionally, food recalls cost companies an average of $10 million per event in direct costs, not including reputational damage and lost sales.
The reason? Poor cold chain visibility and management.
For years companies have relied on traditional methods and tools to monitor the cold chain. But that came with some clear challenges like limited upstream visibility, manual and random temperature checking, and incomplete traceability. The product would likely already be damaged by the time they spotted an issue, such as temperature fluctuation.
Even if they used state-of-the-art technologies like IoT, carrier sensors, and GPS, the systems operated in silos, which made monitoring difficult.
In industries, such as food and beverages, and pharmaceuticals that are subject to strict regulations, companies can no longer afford to be reactive in their monitoring and response.
That’s why companies need a proactive solution that efficiently minimizes exceptions. They need a unified system that provides all stakeholders across the cold chain with real-time data on temperature fluctuations and routes.
For example, an IoT sensor in the cold storage box should provide stakeholders with real-time data on temperature and location, and alert them to exceptions, such as extreme temperature fluctuations. AI should optimize routes and reduce waiting time.
A cohesive approach like this will help stakeholders respond proactively to exceptions and ensure compliance.
In this blog, we will explore how companies can build such unified systems, minimize exceptions, and improve ROI.
How CSCS Helps Companies Integrate AI and IoT?
There are many components involved in maintaining the cold chain.
The IoT sensors are directly placed inside the transport unit, like a reefer truck or trailer, provide real-time temperature readings.
The GPS trackers provide the exact location and vehicle status, such as door openings and engine hours.
The carrier APIs offer scheduled and estimated transit data.
CSCS integrates these components to provide a unified interface for stakeholders.
Here’s how it works:
Trackers on pallets stream live condition data, combined with reefer readings, to give a clear picture of what’s happening inside every trailer.
CSCS ties this data directly to purchase orders, WMS, ERP, carrier feeds, and trading partner platforms. Automated workflows handle compliance in the background so nothing is missed.
Everyone from warehouse teams to carriers to customers sees the same source of truth. With SCOTI, our AI engine, that data turns into clear actions: smarter routes, faster turns, less spoilage, and tighter inventory control.
By unifying these systems, companies can more effectively predict and manage exceptions.
For example, if GPS data indicates that a vehicle is moving slowly, the platform can automatically adjust the arrival time and suggest a re-route. Similarly, if the dwell time at a hub or port is excessively long, the platform can alert the yard manager to expedite the release process.
This will help companies ensure on-time, in-full (OTIF) delivery and improve cost savings.
How To Manage Exceptions During Warehouse-to-Transport Handshake?
Platforms like CSCS are helpful during the critical warehouse-to-transport handshake. They integrate various systems, such as WMS and TMS, to provide all stakeholders, including warehouse staff and transport partners, with real-time information about the product.
This ensures that the products are safely transferred from a warehouse to a vehicle without any bottlenecks, such as temperature fluctuations.
Here’s how the platforms support warehouse-to-transport handshake:
Coordinate dock schedules
The platform automates dock scheduling by allowing carriers to manage dock appointments based on the transportation plan, availability of inventory, and labor. This eliminates the need for manual intervention and prevents dock congestion.
Stage goods for transport
At this stage, the platform assists staff in temporarily picking and organizing products near the docks before loading them onto a vehicle. The platform automates picking and loading, and stages products based on the transportation plan, specific routes, temperature fluctuations, and product sensitivity. The objective is to minimize the exposure time on the dock and safeguard the product.
Ensure reefer readiness
Before loading the products, the carrier’s reefer unit is pre-cooled to set the exact temperature. A thorough inspection is done to ensure the reefer unit is working correctly and has sufficient fuel and power. The temperature control system, airflow, and door seals are checked thoroughly to prevent non-compliance. To check all these factors in real-time, platforms like CSCS integrate with IoT sensors. The platform alerts every time there is an exception, such as a shock violation, extreme temperature deviation, or instances of frequent door openings. frequently.
Manage live transport plans
Once the vehicle is loaded, companies can track its route and status in real-time and make adjustments to prevent product damage. They can track the vehicle’s location, adjust dock schedules, and monitor the temperature fluctuations throughout the journey. This will help companies transport the products safely in a stable environment.
Conclusion
Integrating AI and IoT is crucial for reducing costs and generating higher ROI for cold chain products. However, it is not a one-time process or something that can be done overnight. Companies need to start small and scale as they grow. Here’s what companies should do.
Choose one lane or product for the pilot project
Companies can start by choosing one lane for transporting temperature-sensitive products or selecting a product that is susceptible to spoilage due to temperature fluctuation. This will help companies monitor the impact and demonstrate the value of the solution to stakeholders. Use a platform like CSCS with pre-built integrators to connect IoT sensors, WMS, TMS, GPS, and other systems.
Tune alerts
Start collecting the data to establish the baseline performance. This is important because it will help companies differentiate between normal conditions and exceptions and train the staff to focus on only genuine, high-priority alerts. For example, the alarm should not set off if the vehicle doors are opened for loading. It should alert the staff only during a deviation, like the door opening during transit.
Scale without drowning in data
Once the pilot is successful, companies can consider scaling it to other routes and distribution centers. They can establish and standardize new processes, design new automation workflows, and integrate more systems to create a unified view. However, with new data entering the system, there is a risk of staff being overwhelmed by data and false alerts.
This could lead to the staff responding to non-critical alerts and getting overwhelmed. However, with advanced AI and by prioritizing key alerts, companies can focus only on meaningful exceptions.
By taking a phased approach, companies can reduce exception handling and wastage, ensure safe deliveries, and boost consumer confidence.
At CSCS, we help companies integrate IoT and AI, enabling them to gain better visibility and control over their supply chains.
Planning to safeguard your products from temperature fluctuations and other unpredictable factors? Contact us for more information.
Frequently Asked Questions (FAQ)
Q. Why are losses high in cold chain logistics?
Losses mount in the cold chain because products are highly sensitive to temperature, handling, and time. A few degrees of drift, an unnoticed door opening, or extended dock dwell can shorten shelf life or spoil entire loads. Most companies already collect this data, but it often lives in separate systems—reefer telematics here, shipment trackers there, and warehouse logs somewhere else. Without a unified view, exceptions go unnoticed until it’s too late. The result is billions of dollars lost each year in wasted product, claims, recalls, and customer trust.
Q. Why is manual intervention not advisable in cold chain logistics?
Manual monitoring simply can’t keep up with the speed and sensitivity of modern cold chain operations. Staff cannot realistically track every temperature deviation, location update, or compliance requirement in real time. By the time someone spots a problem on paper or in a spreadsheet, the product is often already compromised. Automation ensures that the right people get alerted to the right issues at the right time, reducing waste and preventing costly mistakes.
Q. How can AI and IoT improve cold chain exception management?
While IoT sensors provide real-time insights, AI uses the data to optimize routes, minimize dwell times, and shrink exceptions. It reduces wastage and boosts ROI.