Automated Test Platform for IoT Lighting Systems: A Case Study
Technology Category
- Networks & Connectivity - WiFi
- Sensors - Optical Sensors
Applicable Industries
- Equipment & Machinery
- Telecommunications
Applicable Functions
- Quality Assurance
Use Cases
- Experimentation Automation
- Smart Lighting
Services
- Testing & Certification
The Customer
Customer is an unrivaled industry leader in lighting technology
About The Customer
The customer is a US-based industry leader in lighting technology. They offer a wide range of pioneering LED lighting and related solutions. They have developed a proprietary wireless mesh networking protocol for their IoT-led outdoor lighting systems. These systems are used in a variety of settings, including parking garages, airports, restaurants, and roadways. The customer's commitment to innovation and high-performance solutions has made them an unrivaled leader in their field.
The Challenge
The customer, a US-based industry leader in lighting technology, had developed a proprietary wireless mesh networking protocol for their IoT-led outdoor lighting systems. These systems were used in various settings such as parking garages, airports, restaurants, and roadways. However, the functional testing of each wireless network for these diverse IoT devices became complex and adversely impacted the customer’s scalability and cost-effectiveness. The challenge was to build a test strategy that automated testing of their wireless outdoor lighting product line while sustaining the quality of their high-performance solutions.
The Solution
Softdel designed a highly intuitive automated testing engine to simulate testing for multiple units and systems in a controlled environment. This solution assisted in automated test execution, log file creation, and test report management. An intuitive visualization dashboard was also developed to provide detailed visual reports of testing results, key insights, and focus areas. Additionally, Softdel designed a defect tracking and reporting tool that automatically tracks and reported defects in the customer's outdoor lighting solutions. The technology used included wireless mesh networking, Python programming language, Pytest framework, JIRA for defect tracking, and TestRail for test case management.
Operational Impact
Quantitative Benefit
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