Our customer is a leading “robotics as a service” company based in Silicon Valley. They are RaaS consultants that enable mid-sized American manufacturers to deploy and scale automation quickly and without risk. Detailed information about the client cannot be disclosed under the provisions of the NDA.

Challenge

This B2B project aims at providing robots to organizations that want to automate their processes.

Innowise faced the challenge of developing a practical cloud robotics solution to cover the problems with robot maintenance, data collection on robot performance, and timely repair services. In addition, it was essential to track the robot’s actual operating hours for automatically generated invoices.

Solution

Innowise has developed a SaaS solution for the effective management and seamless integration of robots. Also, we designed an easy-to-use mobile app to enhance the management experience.
Innowise opted for a cloud microservices architecture for the project because it makes applications easier to scale and faster to develop. This architecture closely interacts with AWS - the world's most comprehensive and broadly adopted cloud platform.

Connected AWS services

The complex and multifaceted structure of the solution integrates a variety of AWS services, such as:

Elastic Beanstalk helps you deploy and manage web applications with capacity provisioning, app health monitoring, and more;
DynamoBD supports data structures and key-valued cloud services. The benefits are manifested in auto-scaling, in-memory caching, backup and restore features;
AWS Grafana enables you to query, visualize, and alert on your metrics, logs, and traces that come from the robot;
IOT SIteWise – a managed service that collects, processes, and monitors robot data locally – even without an internet connection;
IAM securely controls access to AWS resources and manages permissions;
SNS is used to send SMS notifications to customers and developers about the critical states of robots;
SQS for Celery – asynchronous task queue based on distributed message passing;
KMS to store and auto-refresh keys;
RDS (PostgreSQL), S3, Lambda are implemented to send the connectivity status of the robot to the back-end;
SES is a cloud email service for bulk email sending;
KVS – for secure live streaming.

In addition to the services listed above, the Django service deserves special attention since it can accumulate data from robots, compile daily and monthly invoices, and draft contracts with clients detailing only the idle time.

Smart checking of current robot status

To understand the current status of the robot, we set up a system that compares the current set of robot data with some previous ones. If the anomaly is detected, it receives a status – “severe” or “warning” – and sends a push notification to the appropriate communication channel.

Also, the third-party service IXON allows monitoring the performance of robots in real time. Since robots are registered in StrideLinx, it is possible to modify the router’s configuration remotely, find out what devices are connected to it, etc.

GitHub actions for CI/CD

The code is pushed to the elastic container registry, and then the CD deploys the changes in the dev and main branches to the appropriate environments in Elastic Beanstalk.

In Elastic Beanstalk itself, we have set up automatic health checks of the environments which send alerts to Slack if the environment is troublesome.

Datadog for storing logs

Datadog brings together end-to-end traces, metrics, and logs to make robots and AWS services entirely observable. Currently, Innowise is working on switching to AWS SiteWise to store robot data since it will solve the problem of the loss of internet connection. This solution prevents robot data from being lost and sends it to the AWS server even when there’s no internet connection or the back-end is unavailable.

Mobile application

Our team has developed a mobile app that allows customers to get up-to-date information about the status of the robot they have rented. There are also handy graphs in the application that show robots’ idle and working times.

Thanks to the integrated WebRTC based on AWS KVS, the customer can also connect to the robot’s camera and see what the robot is currently doing.

Technologies & tools

Embedded

PLC, Robot controller, LoRaWAN, MicroPython, OPC UA, Raspberry PI, ESP 32

Front-end

TypeScript, React Native, Redux, react-navigation

Back-end

Python, Django, Celery, Celery beat

Cloud

Elastic Beanstalk, DynamoDB, AWS Grafana, IOT SIteWise, IOT core, IAM, SNS, SQS, KMS, RDS(PostgreSQL), S3, Lambda, SES, KVS

VCS

Git, GitHub

DevOps

GitHub Actions. DataDog, Nginx, Docker, Docker Compose

Process

After collecting and documenting the client’s requirements, Innowise began development. We used the Scrum approach with one-week sprints and meetings three times a week to discuss important issues. Slack and Jira were used to manage tasks and discuss projects within the team. Each week, the project manager reached out to the client via Skype to provide an update on the development process.

Team

Project Manager

Back-End Developers

Front-End Developer

Robots Support Specialists

Results

As a result, Innowise developed a solution that increased manufacturers’ demand for robot rentals.

Since we implemented “robot as a service” in cloud computing, the customer can monitor the robot’s status in real time and provide timely technical support. With AWS SiteWise connected, all robot data is saved and displayed correctly in invoices.

Also, companies that rented robots from our client found that their production efficiency increased by 40%.

Project duration

January 2022 - Ongoing

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Robot as a service in cloud computing: 40% efficiency increase and 20% growth in customer base

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Robot as a service in cloud computing: 40% efficiency increase and 20% growth in customer base

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