AI-Powered Inventory Scanner Mobile Application
Budget: $10,000 – $20,000 USD
Read the entire description, those that have not read the entirety of the description will be denied, we are looking for serious applicants:
Overview:
The primary objective of this mobile application is to provide a convenient and efficient solution for inventory management, specifically tailored to the unique requirements of Firehouse Subs franchises. The app will leverage the power of artificial intelligence to identify and count various inventory items in the refrigerators and back-of-house areas. Additionally, it will generate automated reports, enabling you to streamline inventory counting and significantly reduce the time-consuming manual process.
Key Features:
AI-Powered Inventory Scanning: Employees will be able to download the mobile app and, by entering their store code, gain access to the inventory scanning functionality. With a simple process of capturing images or scans of inventory items, the AI algorithm will identify and count each individual item accurately.
Seamless Reporting: Once the AI has processed the images or scans, the mobile app will automatically generate a comprehensive report. This report will be promptly sent to the store owner via email or text message, providing an instant snapshot of the total inventory count.
Training Mechanism: The AI system will be trained to recognize various meats, sauce containers, boxes, and other items typically found in Firehouse Subs franchises. It will possess the capability to identify items based on size, color, labels, and even unconventional placements. The training mechanism will ensure continuous improvement of the machine learning algorithm, gradually increasing its success rate to 100% regardless of item placement.
Versatile Image Recognition: The app will support image recognition at all angles, enabling employees to capture pictures of the inventory from various perspectives. To facilitate this, checkboxes within the app will guide employees on which angles need to be covered for each refrigerator shelf.
More importantly:
There needs to be a mechanism so that we can train the AI on all of the meats, sauce containers, boxes, and more; the AI should be able to identify these items regardless of their placement. There are different types of meats, containers and packages; the AI should be able to identify all items based on size, color, and labels;
sometimes the meats are thrown in random places by the workers, the meats are also at times stacked in front of each other, and with a front facing picture/scan of the refrigerator, there would be no way of knowing which meat is behind the one in front, to combat this the AI should be able to detect the shelf space based on how far the first item is distanced from the front of the refrigerator, based on this reading it should be able to count the projected meats behind the first meat. We can combat this further by simply taking vertical (top view) pictures within the refrigerator for each shelf, the AI should be able to count items at all angles. There should also be checkboxes within the app signaling to the employee on which angles need to be covered for their refrigerator scans.
Overview:
The primary objective of this mobile application is to provide a convenient and efficient solution for inventory management, specifically tailored to the unique requirements of Firehouse Subs franchises. The app will leverage the power of artificial intelligence to identify and count various inventory items in the refrigerators and back-of-house areas. Additionally, it will generate automated reports, enabling you to streamline inventory counting and significantly reduce the time-consuming manual process.
Key Features:
AI-Powered Inventory Scanning: Employees will be able to download the mobile app and, by entering their store code, gain access to the inventory scanning functionality. With a simple process of capturing images or scans of inventory items, the AI algorithm will identify and count each individual item accurately.
Seamless Reporting: Once the AI has processed the images or scans, the mobile app will automatically generate a comprehensive report. This report will be promptly sent to the store owner via email or text message, providing an instant snapshot of the total inventory count.
Training Mechanism: The AI system will be trained to recognize various meats, sauce containers, boxes, and other items typically found in Firehouse Subs franchises. It will possess the capability to identify items based on size, color, labels, and even unconventional placements. The training mechanism will ensure continuous improvement of the machine learning algorithm, gradually increasing its success rate to 100% regardless of item placement.
Versatile Image Recognition: The app will support image recognition at all angles, enabling employees to capture pictures of the inventory from various perspectives. To facilitate this, checkboxes within the app will guide employees on which angles need to be covered for each refrigerator shelf.
More importantly:
There needs to be a mechanism so that we can train the AI on all of the meats, sauce containers, boxes, and more; the AI should be able to identify these items regardless of their placement. There are different types of meats, containers and packages; the AI should be able to identify all items based on size, color, and labels;
sometimes the meats are thrown in random places by the workers, the meats are also at times stacked in front of each other, and with a front facing picture/scan of the refrigerator, there would be no way of knowing which meat is behind the one in front, to combat this the AI should be able to detect the shelf space based on how far the first item is distanced from the front of the refrigerator, based on this reading it should be able to count the projected meats behind the first meat. We can combat this further by simply taking vertical (top view) pictures within the refrigerator for each shelf, the AI should be able to count items at all angles. There should also be checkboxes within the app signaling to the employee on which angles need to be covered for their refrigerator scans.
Related categories:
Mobile App Development
iPhone
Software Architecture
Machine Learning (ML)
Artificial Intelligence