Optimization of Transportation Using ML and AI

AI is a technology that gives machines the ability to think like humans. AI-enabled machines can imitate humans, automate manual chores, and learn on the fly in the same way that humans can.

ML and AI have become an integral part of realizing smart transportation. In this context, using an improved deep learning model, the complex interactions among roadways, transportation traffic, environmental elements and traffic crashes have been explored. The proposed model includes two modules, an unsupervised feature learning module to identify the functional relationships between the variables and the feature representations and a supervised fine-tuning module to perform traffic crash prediction, best flight and hotel price prediction.

• Smart Travel Assistants – With the help of virtual travel assistants, data analytics assists customers to opt for better choices. Also, certain digital applications use AI to automate repetitive tasks and ML technology via chatbot systems provides assistance to the customers.
• Flight and Hotel Price Prediction – Forecasting AI and Data Science tools will automatically monitor the market and send notifications with the significant best deals available. The addition of such a tool to an online travel agency’s portal provides an edge to its sales and also tempts customers to book more trips.
• Optimizing Disturbances in Management – The technology also resolves obstacles that travellers might face during their travel. It can automatically handle roadblocks in the plan. AI advancements along with predictive analysis provide an edge to prevent obstacles even before they occur.
• Interactive Customer Support – ML and AI chatbots are an interesting way to optimize various aspects of customer service and assistance. Through a custom programmed chatbot, customers can be provided with basic informational and transactional services for a smooth experience.
• Customized Offers for Valuable Customers – AI tools generate a strong model for offering a great deal to loyal clients by gathering the details from legacy data and customer activities.
• Customer Sentiment Analysis Through Social Media – Big data, ML and AI can help travel agencies track what customers are saying about the company on social media platforms. This can help the organization to review the negative responses and improve the issue identified by customers. With the deployment of supervised learning and natural language recognition, data tools can trace the negatives from social media conversations and address them with positive responses.
• Hospitality Industry Pricing – Fluctuating price market is one constant change that affects the hospitality industry in various ways. Machine learning technology can be used for dynamic pricing and enhance the potential and effective profitability of such schemes.
• Customer Experience – Even after Booking a service, AI can assist post-booking activities as well. Virtual assistants can be utilized inside hotel rooms to control room lights, electronics or provide validation through facial recognition while check-in.