How AI and IoT can transform the logistics and transportation management ecosystem?

Before the first car was developed by Henry Ford in 1908, all shipments were handled by carriage and horses. Companies had to struggle with low security and poor efficiency using these methods.

When the cars started to appear in the markets and on roads, people started using them for the delivery of goods. It resulted in a lesser time to ship products and reduced logistics costs. Later at the end of the 20th century, logistics experienced a dramatic change that transformed the delivery process: logistics software. Since then, technology has taken over the execution and planning of multiple tasks, including paperwork and manual workflow, while securing vulnerable information.

Technology is continuously disrupting the logistics sector and changing the way how freight, sales orders, materials, goods, production and inventory are managed. Businesses always look for a solution that can bring intelligence to the logistics operations workflow and help reduce high costs.

As speed, intelligence and efficiency became the significant determining factors; the logistics sector has adopted emerging technologies, including AI, IoT and blockchain, to meet the rising demand and deal with complex processes.

Let’s discuss how to develop custom logistics software for logistics and transportation management using AI and IoT.

Logistics and Transportation Management

Logistics and Transportation Management is a field that needs analysis and precision. It controls the delivery of goods or materials from suppliers to customers. It is the responsibility of logistics professionals to focus on transportation, basically, the procurement and planning of transportation for goods and materials.

Logistics and Transportation Management System mainly handles the following components:

  1. Pickup and Delivery Request
  2. Carrier Management
  3. Pickup Optimization
  4. Warehouse Management
  5. Transit
  6. Delivery
  7. BI and reporting

1. Pickup and Delivery Requests

The role of a customer is to assign pickup and delivery requests that go to the carrier.

Here’s how you can develop an interface for customers to send pickup and delivery requests.

You don’t need to develop a new solution for managing the pickup and delivery of goods from scratch. There are many logistics software available in the market, including NetSuite and McLeod, that can be used to handle the operations effectively.

  • NetSuite
    NetSuite is one of the popular platforms for logistics operations that facilitate integrated forecasting and budgeting, supply chain and inventory, revenue management, customer relationship management and business intelligence.
  • McLeod
    McLeod provides trucking software and transportation management solutions to the trucking companies and allows trucking dispatch operations management, document imaging, fleet management, business process automation and EDI.You can use the above solutions to handle the pickup and delivery requests. When the customer sends the requests for pickup or delivery, the request is sent to the carrier who assigns the shipment to different drivers.It becomes essential for carriers to analyze if the pickup or delivery is completed on time or how many times the driver deviates from the planned route. It can be possible by implementing AI and IoT to the logistics software.

Gartner has predicted that 50% of the large global companies will use advanced analytics, IoT and AI in their supply chain operations.

Let’s understand how emerging technologies can ensure the on-time pick up and delivery of goods.

2. Carrier Management

Using Predictive Analytics algorithms, carriers can identify if the deliveries are done efficiently or not.

  • Predictive Analytics ensuring On-time and In-Full Delivery 

Real-time predictive logistics analytics ensure that fleets arrive on time, goods are received and moved on time so that shipments are delivered to customers when they want it.

Sensor-enabled assets or IoT devices embedded in trucks, trains or ships feed data like engine performance and speed and send it to the carriers who can model and predict the estimated arrival times and engine failures. For example, telematics data captured from a vehicle can reveal its speed, position, condition and time left to reach the destination.

The captured data can be used to notify receivers of delays along with the load/unload activities, trucks heading to the same destination and product delivery requirements. As a result, it ensures minimized delays and fulfilled customer expectations.

Smart logistics using AI and IoT helps ports, shipping companies, suppliers and agents optimize resource utilization and their schedules.

  • Logistics Demand Forecasting based on Inventory and Orders Data

With Logistics Demand Forecasting, companies can anticipate the demand for shipments and products across the supply chain. Logistics companies need to implement a forecasting model to evaluate capacity demand based on the combination of historical data, including inventory data and order data.

With custom demand forecasting models, companies can achieve an accurate forecast that helps them understand the level of additional capacity required, reduce the kilometers spent repositioning assets and improve cargo vehicle capacity and asset utilization.

Since the logistics companies can forecast asset and shipment demands accurately, they can increase cargo capacity and high-demand goods can be delivered to customers on-time.

  • Automatic IoT and AI-Driven Shipment Notification

Implementing IoT sensors in logistics makes tracking of goods more accessible. Sensors are used to capture and exchange data. IoT allows handling data remotely across the network infrastructure.

For example, sensors can be embedded in vehicles carrying goods from one place to another. Data captured by sensors can be converted into valuable insights using AI.

AI-enabled analytics facilitate tracking of shipments from departure points to the final destination and send tracking reports during the journey. Real-time monitoring of goods provides information, including:

  1. Tampering or theft during the journey
  2. Departure and arrival times
  3. Live location of the shipment
  4. Any deviations from the scheduled route

With all the information in hand before the shipment reaches the destination, logistics companies can improve the pick-up and delivery of orders.

The data captured during the supply chain of goods can also forecast future demand that helps in product development and supply and demand planning. As soon as the product is reached at the final destination, manufacturing companies can continue to optimize the production of goods.

Let’s consider the example of processed food items. Different types of sensors can be used to monitor the food production state, the temperature under which they are kept and shipping time. Hazard Analysis and Critical Control Points Checklists are used throughout the manufacturing, production and delivery procedures to ensure that the quality of food is not hampered.

IoT sensors send useful data related to the food within the supply chain, enabling companies to put into practice food safety solutions. It not only helps in meeting food safety regulations but also maintaining customer loyalty and trust with complete transparency.

Another role of the carrier is to provide the optimized routes and interact with warehouse owners for the organized delivery of goods.

Optimizing the carrier route using smart technologies, including AI and IoT, can improve logistics operations and reduce the time to pick up and deliver goods.

IoT provides real-time insights that can be monitored and reported. With remote monitoring capabilities, it becomes easier to identify if there are any delays due to adverse weather conditions or maintenance issues with trucks. Therefore, carriers can be monitored effectively throughout the supply chain.

We shall now explain how optimized route planning using AI and IoT can offer benefits to the logistics companies.

  • Optimized Route Planning Using AI and IoT

Loads can be assigned for pickup to drivers based on their current location. Drivers nearby the pickup location are assigned tasks for picking up goods and drivers get notification about the optimized route to reach the warehouse.

Based on the type of goods to be picked up, for example, perishable or non-perishable products, trucks and warehouses are selected for exchange or delivery.

Trucks equipped with IoT sensors provide real-time analysis of route optimization, ensuring reliability and reducing transit times. Information and alerts captured by sensors are sent to logistics service providers.

Information provided by IoT sensors include:

  1. Type of Goods
  2. Real-time location of the carrier
  3. Deviations from the planned route
  4. Pickup/Delivery to Warehouses
  5. Temperature/Humidity

Implementing AI on the gathered data can help predict the following factors:

  1. Estimated delivery time
  2. Driver behavior analysis
  3. Quality of items, for example, perishable goods
  4. Differences between planned route and the actual route

Capturing and analyzing the data would help logistics companies cut down unnecessary costs, improve the time to pick up and deliver goods and provide the optimized routes. It becomes possible to understand how the actual path is different from the planned one and what could be the reasons behind deviations from the planned route. As a result, AI and IoT combined forecasts more optimized routes for delivery and pickup in the future.

With optimized route planning, it can be possible to plan transit and exchange. Since warehouses can get information about the drivers’ estimated time of arrival, they can efficiently plan for the transit of goods. For example, tools and labor required for the unloading of goods at the warehouse can be arranged in advance so that transit/exchange could be done quickly.  

3. Pickup Optimization

It is essential to optimize the pickup of orders so that products are not affected under any circumstances. Technologies, including AI and IoT, can ensure optimized pickup.

Trucks are selected for pickup based on the type of load to be carried. AI learns historical patterns and allows carriers to make decisions precisely. Based on types of goods to be transferred, an AI-based model predicts the right truck for picking up goods.

For example, if you need to pick up perishable goods or sensitive goods that require extra care, you can plan the pickup of goods in IoT-enabled trucks.

IoT enabled trucks can gather the following data about products:

  1. The temperature under which goods are stored
  2. Real-time location of the product
  3. Humidity exposure during transport
  4. Truck data, including speed, fuel expenses

The data is shared with the logistics companies and product owners so that they could monitor the quality of products is maintained throughout the supply chain cycle.

4. Warehouse Management  

  • Truck and Warehouse Collaboration

     

    1. Load Preparation
      AI and IoT combined can facilitate carrier and warehouse collaboration by connecting them. For example, IoT sensors equipped in a truck sends the real-time location of the truck and its ETA to warehouse managers. Using the information provided by sensors, warehouse managers can keep the required space vacant and prepare for the unloading of goods before time. It will help warehouses manage their schedules efficiently and precisely. Load and unload preparation can be done timely with intelligent prediction using AI. As a result, the wait time for both logistics companies and warehouse operators gets reduced.
    2. Door Planning
      Sensors installed around the warehouse area would send the information related to doors near the vacant space to truck drivers based on their GPS data and estimated time of arrival. It will help truck drivers reduce the time to find the right door to get a quick entry into the warehouse.

      Therefore, AI and IoT also allow the hassle-free door planning to facilitate better collaboration between logistics companies and warehouses.

  • Security and Compliance
    It is essential to prevent drive-aways during the unloading/loading of goods from the truck. To ensure safety, you can use IoT-enabled locks that facilitate interlocking of the trailer’s air brakes with the dock door. Smart locks ensure that the truck cannot depart until unloading/loading gets completed. Trailers can only leave the warehouse when the dock door is closed. It can keep your equipment and employees safe.

     

    Another way to enable the security of the warehouse is by using computer vision. IoT cameras can be installed in the warehouse area that captures the status of loading /unloading and load transfer. Edge computing can be applied to the smart cameras that enable the crucial action based on any event fetched during load transfer activity.

    For example, if any fragile good gets broken up during unloading due to the bad behavior of labor, warehouse managers can get notified and action can be taken against that person.

5. Transit

Transit operations can be transformed using IoT-enabled sensors and AI technology. GPS sensors installed in trucks provide its real-time location based on which AI model evaluates the estimated time of arrival.

IoT sensors equipped in trucks can capture information, including crash incidents, the temperature under which goods are kept and humidity. Based on the real-time data gathered by IoT devices, logistics companies can track transit operations in real-time.

Implementing predictive analytics would help companies understand the difference between predicted time and the actual time the truck takes to reach the destination. Customers and logistics companies can know if the goods are delivered under the right temperature conditions.

  • Load Exchange Optimization
    In case, the truck gets overloaded or meets with an accident, truck drivers have to wait for a long time to find alternative options. But IoT and AI can help reduce the wait time by capturing real-time data and enabling intelligent actions. AI-based models for load exchange optimization can be implemented to allow the quick exchange of load from one truck to another.For example, if a truck meets with an accident, IoT sensors would capture this information and a new vehicle will be assigned automatically to exchange the load and deliver it to the final destination.GPS devices installed in the truck provide information, including latitude and longitude, real-time location of the vehicle and motion of the vehicle. Therefore, carriers can quickly determine the condition of a vehicle during an accident or mishappening and arrangements for exchange can be made accordingly.

That is how emerging technologies ensure the seamless transit and delivery of goods.

6. Delivery

The next step in the process is to deliver the goods to end-customers. The carrier would go to the warehouse to deliver goods to end customers. Similar to the above process, trucks would be notified about the vacant door for picking up goods and warehouse operators would be informed about the load preparation.

The load will be transferred to the carrier under the complete security using IoT-enabled locks and computer vision-based cameras. Once the loading is done, the carrier would depart and the goods will be delivered to the customers.

7. BI and Reporting

Once the pickup and delivery of products are done, companies would need a comprehensive report that would contain the negative and positive trends of performance during the supply of goods.

Since companies require granular transparency into their transportation expenses for managing and controlling them effectively, the demand for business intelligence within the logistics and transportation space is skyrocketing. They want to identify root causes and analyze negative trends in performance and cost to take intelligent actions.

Business Intelligence allows converting data into valuable information. Earlier, reporting was only limited to extracting data, fetching it from a system and bringing it into a spreadsheet or database where a company would try to use it and convert it into useful data.

But nowadays, business intelligence has reached the next level, where companies can generate valuable reports that showcase all the data about logistics providers in a scorecard format. Factors, including on-time pick-up and delivery, capacity commitments and driver behavior are assigned metrics that help users determine the performance of carriers.

Also, managers who require a daily and quick overview of what is happening can use real-time dashboards that provide real-time information and help users solve problems as they occur. Dashboards offer companies the advantage of quick reaction time as users don’t have to wait for someone to create and send reports.

Companies use BI and reporting to display patterns found in historical data that can predict opportunities and future risks in the supply chain or transportation networks.

Let’s understand how shippers can use business intelligence to improve logistics and supply chain operations with an example.
Suppose one shipper has a 90-percent on-time delivery rate for load transfer consistently, but he wants to go to the root of the problem dragging down the other ten percent of shipment. Did delays occur because of the broken lanes? Is there any problem with the equipment or carrier?

With business intelligence, it becomes possible to narrow down delay-causing factors. For example, if the shipper reached late due to the congestion in that way, companies can discover the issue with business intelligence and take necessary actions.

With BI data, it becomes easier for logistics companies and their team to make operational decisions more efficiently.

Therefore, implementing BI across the shipments can result in an end-to-end pickup and delivery time improvement.

Conclusion

Artificial Intelligence and the Internet of Things are disrupting logistics and transportation management by making logistics operations more smarter day by day. It is expected that delays in pickups/deliveries and trucking capacity concerns will be a matter of the past when AI and IoT come into the picture.

If you are looking to build the custom logistics software for your company that implements AI and IoT, our experts can help you develop smart software for your business needs.  

Author’s Bio

Akash Takyar
Akash Takyar
CEO LeewayHertz
Akash Takyar is the founder and CEO at LeewayHertz. With the experience of building over 100+ platforms for startups and enterprise allows Akash to rapidly architect and design solutions that are scalable and beautiful.
Akash's ability to build enterprise-grade technology solutions has attracted over 30 Fortune 500 companies, including Siemens, 3M, P&G and Hershey’s. Akash is an early adopter of new technology, a passionate technology enthusiast, and an investor in AI and IoT startups.
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