The role of AI and IoT in transportation isn’t limited to self-driving cars or road traffic management by cities. People in logistics are adopting these novel technologies to optimize their processes and overcome traditional obstacles not addressable by legacy solutions.
The Internet of Things (IoT) refers to any object that becomes smart by connecting to the internet and communicating with other devices on the same network.
Cities and municipalities use IoT to manage traffic and enforce traffic regulations. For example, cameras, smart parking, and automatic traffic lights send data to IT centers to find patterns, find drivers who violate rules, and reduce the risk of accidents.
The same thing applies to transportation and logistics management. Logistics and supply chain companies can use IoT to improve their efficiency using real-time data. In doing so, a combination of smart and embedded devices, networking systems, and IoT services works toward optimizing different stages of supply chain management.
These objects and devices can also use sensors and actuators to collect data about everyday uses, scenarios, and interactions.
These data are then collected and analyzed to find patterns and help run operations more smoothly. Here’s how AI comes into play. These devices use deep learning and machine learning to learn from their data and help improve operations. They can also send the data to Transportation Management Systems (TMS) and Warehouse Management Systems (WMS) over the cloud to improve performance in a more centralized fashion.
The big data generated by sensors and other IoT devices are a valuable source to predict future trends or account for current ones, helping businesses make decisions faster. Transportation companies can use these data in different ways to solve their issues. Transportation analytics, including descriptive, diagnostic, predictive, and prescriptive data analysis methods each serve a different purpose in improving business operations.
In addition, AI technologies like Natural Language Processing (NLP) help make sense of these masses of data more accurately. Businesses can learn and obtain more precise information from these data to find patterns and predict trends.
The future of TMS platforms is in AI and IoT. They rely on AI to automate their processes in both supply and demand sectors, with the following applications and advantages:
Logistics and supply chain companies can leverage AI and IoT in their warehouses to manage inventory storage and handling. One of the most recent cases is using robots in warehouses to handle orders. Moreover, sensors can optimize space allocation to increase efficiency and speed and keep track of items in the warehouse.
Knowing what exactly you have in the warehouse isn’t something you can do with traditional methods such as keeping manual logs. These methods are time-consuming and can also increase errors and reduce productivity.
AI can help you keep track of the goods in the warehouse and replenish them before you run out. Moreover, it prevents you from purchasing unpopular goods and keeping them in the warehouse, which can lead to financial losses.
Predictive inventory measures allow you to prepare for special occasions like seasonal trends and foresee demands to adjust your inventory. It can also help you devise sales strategies to sell the items that have been in the warehouse for too long.
AI inventory management can also help you detect faulty items in the warehouse and prevent them from getting shipped to customers. All these measures can gain you a competitive edge in the highly demanding supply and chain sector.
The most widespread use of IoT is in fleet management, as trucks and other vehicles can use sensors and other IoT devices more readily. These sensors can track many actions and patterns to help manage and run the fleet more effectively. For example, businesses can keep track of driver behaviors and identify habits that lead to higher fuel consumption.
RFID sensors work without an internet connection and send data from the truck. It’s an invaluable help since it can prevent accidents or unfortunate situations by sending data in real-time, even if there’s no internet connection. By eliminating those factors, fleet managers can identify conditions or behaviors that lead to accidents and increase driver safety.
In addition, if you send pallet cargo, artificial intelligence can help you optimize space allocation and save costs. The algorithms design the layout of placing pallets inside vehicles and avoid empty spaces that waste your money and resources. The same thing can happen for truck space. This asset positioning can save your business considerable operational costs by reducing the number of vehicles that need to be on the road.
When you think of IoT in transportation, self-driving cars pop up in your mind. While autonomous and semi-autonomous trucks are a great part of this vision, they’re not the only IoT-enabled part of the chain. These visions may seem way into the future, but technological advances are happening at such breakneck speeds that even small transportation companies can soon adopt them.
The computer vision technology used in vehicles can detect issues and respond quickly. Gyroscopes, telematics, humidity and proximity sensors, and magnetometers can all help improve safety in one way or another.
Damaged roads, pedestrians, and driver fatigue are among the most common causes of accidents. AI and IoT devices inside vehicles can detect these issues and prevent accidents. They can also get data by connecting to systems belonging to cities and municipalities.
Road condition monitoring systems can notify drivers of the condition of the road ahead, like if it’s slippery or bumpy, and help them prepare to drive safely.
The options are numerous, and each company can adopt the ones that match their conditions to increase safety and save costs by preventing accidents. AI and IoT can also help companies adopt alternative transportation modes, such as drones, to boost safety and efficiency.
Knowing where each truck and its cargo are in real-time is essential in offering fast and reliable services to your customers. Scanning the items is a good way to keep a log of them. However, knowing where they are at each delivery phase is not enough.
IoT devices like radio-frequency identification (RFID) and automatic identification and data capture (AIDC) sensors are more advanced tools that help trace orders. This way, you can show your customers where their order is and when to expect it to arrive.
In addition, temperature, light exposure, pressure, and humidity sensors help keep perishable goods and medicine in optimal condition until delivered to the customer. When the environmental conditions aren’t suitable, the sensors adjust temperature and humidity to keep items fresh. These sensors can detect damaged and defective items and prevent them from getting delivered to customers. Vibration and shock sensors also prevent fragile goods from getting damaged.
Finally, IoT devices help increase security by letting you know where each item is. This will eliminate theft and unauthorized access to cargo. In addition, truck drivers can also have digital IDs that make them easy to identify and give them instant permission once they reach the warehouse.
A significant factor that leads to a waste of resources and reduces efficiency is selecting the wrong roads to deliver goods. Road traffic can reduce driver efficiency and delay delivery, reducing customer satisfaction. AI solutions have been of significant help, most commonly integrated into TMS platforms.
These platforms use data to plan the best route for trucks and adjust the routes in real-time depending on road conditions. As a result, orders can be delivered faster and at lower costs. AI-powered software allows logistics planners to predict weeks of their operations ahead of time, enabling them to respond to adverse weather conditions or unforeseen traffic problems.
In addition, if you have several warehouses, AI can help you send the orders from the nearest warehouse to the customer, saving time and money and accelerating the delivery process.
Route optimization can also minimize the instances of empty trucks returning to warehouses. AI can plan delivery schedules so that the trucks always have cargo to move, optimizing resource allocation and preventing the waste of time and money.
The sensors and other IoT devices used in trucks allow businesses to increase their vehicles’ lifespans. AI uses the data gathered from these devices to predict vehicle problems and suggest periodic maintenance based on the vehicle’s condition.
In addition to lengthening the vehicle’s lifespan, these measures will minimize the risk of on-the-road failure and downtime. The sensors used in vehicles can send alerts on fuel consumption and when to refuel to avoid downtime.
All the above benefits are ultimately supposed to increase customer satisfaction and create a better experience. Whether you have B2B or B2C customers, they stay loyal to your business and are less likely to turn to your rivals to purchase their goods.
Effective inventory management prevents stockouts, and an optimized routing and re-routing logistics plan can ensure that customer get their orders as fast as possible.
Artificial intelligence facilitates communication between the customer and your business, letting them know where their order is during the delivery cycle. Moreover, you can create a more personalized experience for them using AI algorithms that track their previous purchases and suggest related products.
One of the most prominent outcomes of integrating AI into business operations is increased productivity. Artificial intelligence in WMS and TMS platforms automates most daily tasks that otherwise require massive paperwork by employees.
All parties are connected through the same platform, having access to real-time information required for doing their jobs. Even drivers can see the information they need through a mobile app that shows data in real-time.
Logistics planners don’t need trial and error to solve their issues and optimize their processes. Descriptive data analysis allows them to sift through massive data sets and paint a clear picture of their logistics operations. They can rely on other forms of data analysis to plan their logistics accurately.
As the company grows, the amount of available data increases to the point of being uncontrollable. Without the help of AI, it’s impossible to make sense of them. Moreover, AI-powered software can use external factors to help make logistics decisions.
This automation increases employees’ productivity since they don’t need to perform repetitive tasks. In addition, it minimizes errors that are inevitable with human tasks. This way, you can either replace some job roles with AI or give staff more time to focus on critical tasks.
Advances in logistics and supply chain management mean customers can get their orders as fast as possible. Same-day delivery has taken customer expectations to another level, and every transportation business strives to deliver goods quickly. However, these advances take a toll on the environment, increasing carbon footprint and sending too many vehicles on the road.
AI can help reduce carbon footprint by giving logistics companies the best transportation modes to send their items. A company with multi-modal transportation can adjust its vehicle choice based on the lowest fuel consumption and the most efficient roads.
In addition, AI-based TMS platforms analyze the performance of third-party couriers. These analyses help logistic planners choose the best couriers with the highest efficiency.
Most importantly, lowering fuel consumption through route optimization has the highest impact on lowering costs and carbon footprint.
Optimizing pallet space is crucial both in asset positioning and complying with regulations. Logistics companies must weigh their items precisely to ensure they remain within the allowed thresholds. The sensors used in goods and pallets eliminate the need to weigh cargo and avoid lengthy calculations. These sensors can also be used on the truck floor or axles to give the real-time weight of the entire truck.
AI-powered software can also help employees issue paperwork required by regulatory bodies quickly and efficiently. They don’t miss any legal documents, and the chances of fines due to violating regulations will be minimized.