Machine-vision apps for the transportation sector are used to help logistics companies track their shipments. These apps identify, classify, and count items such as packages, pallets, and bottles as they move along a supply chain. Machine-vision apps also detect shipping irregularities such as damaged or misplaced shipments and notify users of potential problems.
Machine vision apps are similar to object detection apps and image recognition apps, and often require image and video analysis capabilities. Examples of machine vision applications include Diagnostic Vision, iRobot Inspection, and the Cognex Lens Wiper Monitor.
A parking street sign app. Camera takes a picture of parking sign and converts that to data. Data is then stored in system with a GPS location. Sends data back to phone to let the person know if they can park there.
A machine vision app can grow its user base within the transportation sector by offering clear value propositions and a vast selection of features for drivers and manufacturers. Vehicle safety is an important concern for consumers, and machine vision apps provide a way to improve the safety of autonomous vehicles, as well as conventional vehicles. Machine vision solutions can also be used to monitor driver behavior and alert drivers when they are not abiding by traffic laws. These additional features can help transport companies save on insurance premiums and increase revenue from clients that require such services.
A machine vision app provides users with visual inspection of physical objects. It can face legal and reputational risks involving the misclassification of objects, the storage of sensitive personal information, and the handling of user data. Machine vision apps should take strong measures to verify user identities and provide users with safety mechanisms for cancelling inspections and reporting platform abuse. It is recommended that machine vision apps provide robust mechanisms for reporting platform abuse and conduct routine security audits to prevent unauthorized access to user data.