California
IoT
1 year
6 members
Our customer is a California based branch of a well-known enterprise company that specializes in solutions for connected devices in the Smart Home domain.
The main goal of the project was to create a system of integrated devices in Smart Home that allows customers to monitor gas, water and electricity consumption remotely via a mobile app and a web dash board.
It took our customer a while to find skilled engineers that specialize in programming for iOT devices. They also realized the importance of proper testing of a solution on the software and hardware side. A lot of equipment was delivered to Eastern Europe from the USA to develop a solution on real devices when the emulators could no longer be used.
Project deliverables were distributed across three sections:
Physical devices embedded with sensors were connected to the Cloud. Devices could be controlled remotely from the Mobile application and a Web Dashboard. Also, system architecture provided real-time monitoring, control, and data exchange between devices, cloud platforms, mobile applications, and web dashboards.
The platform used devices for Smart home automation such as Central IoT controller (gateway), smart sockets, air sensors, water sensors, security sensors, etc.
Team structure
For a year a team of 6 dedicated engineers was working on the project managed by a PM and a product owner from the customers side
Before our customer settle down with our company, it took them a while to find skilled engineers that specialize in programming for iOT devices. They also realized the importance of proper testing of a solution on the software and hardware side. A lot of equipment was delivered to Eastern Europe from the USA to develop a solution on real devices when the emulators could no longer be used.
Front-end:
The front-end part contained (20-25 screens) from Mobile application and (~20 pages) of Admin Management Dashboard .
In the mobile application, it was necessary to implement many graphs and ensure high performance for real-time data
Back-end:
The cloud part had to support a high load (up to 10 M) of messages per second.
Compiled from many microservices and brokers. 3 types of databases were also used - relational, non-relational, and graph
All infrastructure was described with Terraform configs.
Testing of the solution:
Security
AWS RDS
AWS IoT Core
AWS EC2
AWS SQS
AWS Lambda
AWS Timestream
Python
C++
ESP-32
STM-32
Node.js
React.js
Redux
Redux-Thunk
React native
Dynamo DB
AWS Timestream
AWS Dynamo DB
AWS RDS
Circle-CI
Docker
Kubernetes
AWS ECS
Terraform
Manual QA (Hardware testing, Front-end, business logic)
Unit testing (Code level)
Integration tests, Runscope (API)
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