ANI Technologies has been granted a patent for a method of vehicle maintenance at a service center. The method involves retrieving vehicular datasets from a database, determining a service schedule based on the datasets, monitoring the progress of servicing vehicles, and updating the service schedule accordingly. The method also includes using sensor outputs and image recognition to identify vehicles that require servicing, automatically scheduling operations for servicing, and detecting anomalies in the execution of operations. GlobalData’s report on ANI Technologies gives a 360-degree view of the company including its patenting strategy. Buy the report here.
According to GlobalData’s company profile on ANI Technologies, usage monitoring vehicle telematics was a key innovation area identified from patents. ANI Technologies's grant share as of September 2023 was 31%. Grant share is based on the ratio of number of grants to total number of patents.
Method for vehicle maintenance and scheduling at service center
A recently granted patent (Publication Number: US11756005B2) describes a method and system for vehicle maintenance at a service center. The method involves retrieving sensor outputs from a set of vehicles indicating their current health status and storing this information in a cloud-based server. The server also retrieves images of vehicles from cameras at the service center and uses image recognition to identify the vehicle registration numbers. Based on the sensor outputs and recognized registration numbers, the server retrieves vehicular datasets for vehicles that require servicing.
Using various elements from the vehicular datasets, such as identification information, asset health index, probability of brake failure, driver scores, running cost per unit distance, and service interval, the server determines service job data for each vehicle. This service job data indicates the operations that need to be performed for servicing the vehicles. The server then automatically schedules these operations in a sequence that minimizes the total turn-around time for execution. This scheduling is done using meta-heuristic optimization algorithms.
Operators associated with the service center are allocated to execute the scheduled operations, and instructions for the operations are communicated to them through electronic devices. The server monitors the execution of the operations using sensor data and video feeds, and if any anomalies or delays are detected, it automatically changes the sequence of execution for the remaining operations. This reallocation of operations is based on the detected anomaly and aims to optimize the overall execution process.
The system described in the patent includes a cloud-based server that retrieves sensor outputs, stores vehicular datasets, processes images, determines service job data, schedules operations, allocates operators, communicates instructions, and detects anomalies. The system aims to improve the efficiency and effectiveness of vehicle maintenance at service centers by automating various aspects of the process and optimizing the scheduling and execution of operations.
Overall, this patent presents a method and system that leverage cloud-based servers, sensor data, image recognition, and optimization algorithms to streamline and enhance vehicle maintenance processes at service centers.
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