Fleet Management System with Real-Time Load Balancing
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Solution Overview
Problem
Current fleet management systems for vehicles like taxis and limousines are inefficient due to manual data capture, leading to data loss, poor reporting, and errors, and they struggle with real-time communication of multimedia content to multiple vehicles, causing a heavy load on wireless communication links and assuming vehicle availability.
Innovation Solution
A system where fleet vehicles participate in a unique methodology to share information with a central control center, enabling real-time or near real-time data capture, processing, and communication, allowing managers to view vehicle locations and status, facilitate dispatch, and provide electronic trip sheets, using a central control center, gateway, and wireless service provider to handle multiple communication channels securely.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If manual data capture by drivers is used, then implementation simplicity is maintained, but data accuracy and completeness deteriorate
Solution Approach 1:
The system enables self-service data capture where the fleet management software automatically collects trip data, vehicle status, and location information from connected vehicles without requiring manual driver input. This eliminates human error while maintaining ease of implementation through automated processes.
Solution Approach 2:
The patent replaces the mechanical manual data entry process with an electronic automated system that captures data directly from vehicle sensors, GPS, and fare collection systems, substituting human action with automated electronic data collection mechanisms.
2Speed
If simultaneous mass distribution of multimedia content to all vehicles is performed, then real-time communication capability is achieved, but communication link load increases
Solution Approach 1:
The system performs preliminary actions by pre-loading multimedia content to vehicles during off-peak times when communication load is low, and uses predictive analytics to pre-position content based on anticipated vehicle locations and passenger requests, reducing peak-time communication demands.
Solution Approach 2:
Instead of continuous simultaneous distribution, the system implements periodic content updates where vehicles receive multimedia content at scheduled intervals based on their operational status, location, and predicted passenger demand, distributing load evenly across the communication network.
3Adaptability or versatility
If conventional push distribution methodology is used, then content delivery capability is provided, but system complexity and reliability deteriorate
Solution Approach 1:
The system inverts the conventional push distribution model by implementing a pull-based architecture where vehicles and passengers request content based on their specific needs, and the central server responds by delivering only requested content. This reverses the initiation of communication from server-to-vehicle to vehicle-to-server.
Solution Approach 2:
The system dynamically changes communication parameters such as data transmission timing, content format, and delivery method based on vehicle status, network conditions, and passenger preferences, optimizing reliability by adapting to real-time conditions rather than using fixed distribution patterns.
4Ease of operation
If vehicle availability is assumed for content distribution, then distribution simplicity is maintained, but service accuracy deteriorates
Solution Approach 1:
The system implements continuous feedback mechanisms where vehicles report their actual status (available, in-service, offline) to the central management system in real-time, and the distribution algorithm adjusts content delivery based on this feedback, ensuring content is only sent to vehicles that can actually receive and display it.
Data Source
AI summary
A method utilizing real-time location information in a fleet management system. Simultaneous wireless communication connections are maintained between a respectively corresponding number of vehicles in a fleet and a central control center. The messages are received at the central control center, and each one of the messages includes information indicating the geographic location of a respectively corresponding vehicle in real-time or near real-time. The messages are collected and stored in the central control center. In response to a user request, a fleet management tool or report is provided in real-time or near real-time, the management tool or report being based at least in part on the messages indicating the geographic location of the vehicles.


