Remote Food Measurement System

Technology domains

Restaurants & Hospitality

Waitbusters: Restaurant Management Platform Restaurant Inventory Management System Remote Food Measurement System

Waitbusters: Restaurant Management Platform

Running a successful restaurant is a tough job. Many restaurants lose a lot of money and customers, struggling with crowded lobbies, long lines, and paperwork.But the right software can help them overcome these and other challenges to serve guests quickly and efficiently, attract new customers and retain existing ones, and increase revenue while reducing costs.

Restaurant Inventory Management System

On average, restaurants spend around 30% of the monthly budget on food and beverage purchasing. Due to lack of visibility into restaurant stock shelves, around 10% of the purchased food ends up in the trash, which results in huge money loss.Therefore, an effectively functioning restaurant inventory management is one of the most important assets of restaurant daily operations. It helps not only reduce food spoilage but also control and manage restaurant costs.

Remote Food Measurement System

The key to the success of a restaurant chain is an impeccable reputation. When ordering food at a chain restaurant, the customer expects to get a dish with a familiar taste and appearance.That is why the kitchen of such restaurants looks like production lines at large factories. Each step of the cooking process must take a certain amount of time, and each product must have the exact same weight. To achieve this, restaurants need to constantly monitor all stages of the kitchen workflow — from pre-preparation to serving.

Challenge

The key to the success of a restaurant chain is an impeccable reputation. When ordering food at a chain restaurant, the customer expects to get a dish with a familiar taste and appearance.

That is why the kitchen of such restaurants looks like production lines at large factories. Each step of the cooking process must take a certain amount of time, and each product must have the exact same weight. To achieve this, restaurants need to constantly monitor all stages of the kitchen workflow — from pre-preparation to serving.

Since manual tracking is extremely time and effort-consuming, there’s an urgent need for a system that would keep an eye on the cooking process to ensure the ideal quantity and quality of the final product.

Solution

Softarex has designed a Remote Food Measurement System that accurately measures the weight of homogeneous products using video cameras in real time.

The platform consists of:

An iPad application for restaurant operations;
A real-time video stream system based on industrial PC;
A cloud-based web application for data collection and analysis.

Softarex’s Remote Food Measurement System provides the following features:

Automatic food type detection — once a container with food is placed under 3D cameras, the system automatically detects its content and identifies its type.
Product weight measurement — 3D cameras can measure the weight of the identified product in real-time with 95% accuracy.
Containers tracking — monitoring food containers’ movements throughout the kitchen areas.
Time tracking — ensuring food containers stay in the preparation zone for a required amount of time by using counters and alerts for each container that are set either automatically once a container is detected in a particular place, or manually.
Data collection and analysis — collecting data on restaurant food waste and generating kitchen forecasts.
Scalability — the system can cover a chain of more than 2,000 restaurants, maintaining a high level of performance and productivity.

Softarex has provided a tech support team to help our Сustomer speed up the deployment process and create an IT infrastructure that meets the requirements of the developed system.

Project’s results

The Remote Food Measurement System developed by Softarex produced the following results for chain restaurant owners:

The system has revealed that over 30% of food ends up being never served per week;
Fully automated cooking process monitoring;
More informed kitchen decisions based on real-time data collection and analysis;
Optimized kitchen workflow;
Reduced costs.

Technical challenges

Development of software that can accurately identify, track and classify objects in the video stream in real time.

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Meet our
experts

Meet our experts 1/3

Alexander

VP of Engineering

With more than 10 years of experience, I have successfully architected, designed, developed, and implemented mobile, cloud-based, and SaaS applications for the Healthcare, IT, and Restaurant industries. I am passionate about using modern technologies to create useful products that help businesses optimize and automate daily operations, improve connectivity, and make the most out of their data. As VP of Engineering at Softarex, I manage both in-house and offshore development teams hired by Softarex’s clients. I use Agile and Scrum methodologies to encourage continuous improvement of team members and bring transparency and flexibility to projects.

Maksim

System Architect and Delivery Manager

In over 10 years of my professional career, I have developed, architected, and managed dozens of projects for the Manufacturing & Energy, Restaurant & Hospitality, Aviation, and IT industries. I have hands-on experience with Mobile technology, Computer vision, Machine learning, Predictive modeling, Cloud computing, and SaaS. I managed the development of a Computer vision-based kitchen management system for a large restaurant chain. We did a great job on this project, and I ‌consider it the highlight of my career.

Yauheni

Lead Data Science and Computer Vision Engineer

With MA and PhD degrees coupled by multi-year scientific research experience, I am responsible for the development of knowledge-intensive solutions based on Computer vision, Predictive modeling, Deep learning and Machine learning technologies. My responsibilities include planning and managing research, designing software architecture, developing project technical documentation and integrating research results into final products. My team and I always strive to apply the best practices of Computer vision and Machine learning to projects.

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