Please use this identifier to cite or link to this item:
http://localhost:8081/jspui/handle/123456789/18318
Title: | ARTIFICIAL INTELLIGENCE IN TRANSPORTATION AND LOGISTICS |
Authors: | Bhoyar, Sahil |
Issue Date: | Jun-2022 |
Publisher: | IIT, Roorkee |
Abstract: | Artificial Intelligence (AI) has revolutionized the transportation and logistics industry by enabling accurate predictions of total fare and delivery time. With the integration of AI techniques, such as machine learning and predictive analytics, transportation companies can optimize their operations, enhance customer satisfaction, and improve overall efficiency. Predicting the total fare of transportation is crucial for both service providers and customers. By leveraging historical data, AI algorithms can analyze various factors such as distance, route, vehicle type, and traffic conditions to estimate the fare accurately. Machine learning models can learn from past transactions and customer preferences to offer dynamic pricing models, ensuring fair and competitive pricing while maximizing revenue for transportation companies. Additionally, AI plays a pivotal role in predicting the time of delivery in logistics operations. By leveraging real-time data, including traffic patterns, weather conditions, and historical performance, AI models can provide accurate time predictions. These predictions enable logistics companies to optimize their routes, allocate resources efficiently, and provide customers with reliable and transparent delivery timeframes. Moreover, AI-powered systems can dynamically adjust delivery schedules, adapt to unforeseen circumstances, and provide proactive notifications to customers, enhancing the overall delivery experience. The integration of AI in transportation and logistics not only benefits service providers but also enhances customer satisfaction and experience. Accurate fare predictions enable customers to plan and budget their transportation expenses effectively. Reliable delivery time predictions allow customers to track their shipments, manage expectations, and make necessary arrangements. The ability of AI algorithms to continuously learn and adapt from data ensures that the predictions improve over time, optimizing the entire transportation and logistics process. |
URI: | http://localhost:8081/jspui/handle/123456789/18318 |
Research Supervisor/ Guide: | Sharma, S. C. & Pant, Millie |
metadata.dc.type: | Dissertations |
Appears in Collections: | MASTERS' THESES (Paper Tech) |
Files in This Item:
File | Description | Size | Format | |
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21546009_SAHIL BHOYAR.pdf | 3.15 MB | Adobe PDF | View/Open |
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