GuardHat Inc. manufactures a smart hardhat with sensors that continuously transmit data to a safety control center, to process and analyze vast amounts of incoming data in near real time to prevent injury.
In 2016, more than 4000 workers died on the job in the US, and there were nearly 3 million private-sector work-related injuries. Yet a key component of workplace safety, the protective hardhat, has remained largely unchanged over the past 60 years. GuardHat Inc. aims to save lives and prevent injuries with a smart hardhat - a wearable, Internet of Things platform in an industrial hardhat form-factor.
Each helmet continuously transmits data to a GuardHat safety control center for monitoring and rapid response. Because the system collects information from each GuardHat multiple times each second, it generates vast amounts of data. The challenge for the safety control center is to process and respond to this torrent of incoming data in near real time.
GuardHat quickly realized that HPCC Systems could simplify and speed development. It’s an integrated solution, making it easier to learn and use, and GuardHat doesn’t need to spend time bolting together components from multiple sources. “I call it ‘batteries included’” Sengupta says. “Everything that you need is right there. We actually got up and running with HPCC literally over a weekend.” Another key advantage was HPCC Systems’ ECL language: “ECL is a system language across the whole HPCC Systems solution, which obviously plays in as a positive for overall implementation,” Sengupta adds. “We don’t have to learn multiple languages.”
HPCC Systems also meets GuardHat’s other key requirements. The HPCC Systems unique architecture, combining the ROXIE and Thor platforms, fulfills GuardHat’s needs for real-time complex event processing together with big data analytics, Sengupta says. In addition, the solution can scale easily and allows flexible deployment models, with a mix of cloud-based and on-premises systems. Finally, HPCC Systems is a proven open source solution, with great support and a vibrant community, Sengupta says.
All components are included in a homogeneous platform. No additional third party tools are required which simplifies and eliminates complexities from heterogeneous platforms.Real-time Analytics
Ability to handle massively diverse amounts of real-time data combined with built-in analytics libraries for Machine Learning help to quickly extract useful insights from data.Scalability and Rapid Development
Massively scalable data platform supports rapid development from a growing set of real time data sources.Ease of Use
ECL is highly efficient and accomplishes big data tasks with far less code, yet is flexible enough to be used for both complex data processing on a Thor cluster and for a query and report processing on a ROXIE cluster.Integrates Multiple Data Types
Supports multiple data types out-of-the box, including fixed and variable length delimited records and XML. Data model is open for data analyst to define based on business needs without the constraints imposed by strict-key-value store models.