How AI & Machine Learning Are Transforming Logistics
Emerging technologies like artificial intelligence, IoT, and ML have set the logistics sector on a path that will soon transform the trucking industry and give rise to the adaptation of Modern TMS systems.
Where vehicles can move without any human assistance, smart TMS can help you mitigate manual tasks, reduce the use of spreadsheets and the stress of paperwork. AI and cloud-based platforms will shift all the jobs that will increase passenger safety, reduce traffic congestion/accidents, and minimize overall financial expenses.
1- A Rapid Shift to Geo-fencing Technology
Transportation companies are using GPS systems and AI to track the location of trailers/trucks. Modern TMS geo-fencing technology sends you minute-by-minute details of trucks, alerts of drivers in danger to take immediate actions for any mishap, optimizing the routes based on real-time traffic data, changing the hub, or about to reach the destination. The topmost benefit of this technology lies in improving vehicle utilization and automatically tracking driver hours and fuel consumption.
2- A Sudden Rise in TMS Investments
According to recent studies, the global market for AI in transportation is expected to reach 3.5 billion dollars by 2023. Realizing this unique potential of AI, businesses in the transportation sector are making significant investments in AI and cloud-based transportation management platforms to improve revenue generation and stay ahead of their competitors.
3- Practical use cases of AI in transportation increased at a significant level
- Autonomous dispatching, which once was a mere sci-fi fantasy, has now become a practical reality. US logistics are embracing autonomous trucks to decline operating costs.
- Cameras and sensors installed at different locations on the roads collect extensive voluminous traffic data and send it to the cloud, where traffic pattern analysis is performed based on big data analytics and AI-powered digital platforms.
- Traffic flow, road blockage predictions, or any accident information through AI can reduce unwanted traffic, select the shortest route to their destination, improve road safety and reduce wait times.
4- CAGR Growth at a Rate of 45.3 % from 2019 to 2027
In the supply chain and logistics market, AI will grow at a CAGR of 45.3 % from 2019 to 2027 to reach 21.8 billion dollars by 2027. In situations like human errors, traffic, or accidents, AI predicts decisions based on data analysis and helps avoid accidents and maintain their safety.
Fleet management apps will help you observe driver behavior in real-time so that fleet managers can plan the next training accordingly. It will resolve the most common issue of empty miles and long driving hours that affect the finances of trucking companies.
5- AI In Driver App
AI has become omnipresent in our day-to-day lives. For example, every driver has an app that automatically clocks them when they get into a truck and keeps track of their hours, i.e., when they change hubs. Imagine how amazing and exciting a future driven by AI would be! It’s just a glimpse of the possibilities and opportunities that technology can offer.
6- AI in Fuel Management
The impact of data-driven and autonomous dispatching states an opportunity for out-of-the-question levels of optimization.
Transportation firms have started using AI and machine learning for fuel optimization, operational planning & allocation based on Geospatial & status data, dynamic route management, and control.
7- Transparency in Transactions through Blockchain
Blockchain, known primarily as a decentralized digital ledger used for trading cryptocurrencies, is being used by several corporations to optimize their transactions. Not only does this make transactions more safe & secure, transparent, and accountable, it also eliminates the need for vast amounts of operational paperwork.
8- Automated Vehicles Rise in Logistics Industry
AI is beneficial for reducing expenses in logistics. Apart from driverless cars available in the market, AI automates more means of transport like trucks and buses to transport goods.
Conclusion
Apart from the above, AI can be implemented in many other ways in logistics to automate routine tasks, analysis, and narrow their selections to further narrow down the functions to just 2 or 3 within a matter of seconds.
Compared with traditional logistics enterprises, the transformation of artificial intelligence is both an opportunity and a challenge. Presently, there is still a big gap between the logistics industry and the actual needs of intelligent essential data collection and the coverage and accuracy of logistics.
LoadStop Smart TMS tends to fill that gap between the increasing demand for perception facilities like logistics big data and the need for an intelligent platform. Its AI and cloud-based one window solution for the trucking industry wants to shift to modern technologies and speed and accuracy in numerous trucking operations. In any case, it looks like the future is bright for trucking companies that are willing to take advantage of this.
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