Tyler Boyle1
1National Institute of Standards and Technology, Gaithersburg, MD, USA
Flexibility and scalability are often overlooked when designing an Internet of Things (IoT) environmental sensor network. Though accurate measurements are key to a network’s success, in some cases, these measurements can be compromised by using data communications and storage techniques that are not robust and adaptable. In this talk, we will discuss methods used at the National Institute of Standards and Technology (NIST) to address these concerns for our envisioned hybrid greenhouse gas (GHG) detection and measurement network, and how these methods could be applied to any IoT environmental sensing network.
Sensor network architectures used within dense sensor networks have rapidly changed over the last 10 years. We have chosen to use an events-driven microservices architecture, which allows us to make changes to a sensor in the GHG sensing system without disrupting data collection from other sensors within the system. Such architecture is beneficial as it allows for the easy addition of data streams from new sensors or reference-grade analyzers. In this talk, we will discuss the methodologies used to move measurements through the system and the importance of stamping metadata within the measurements. We will also highlight security best practices used to keep both the sensor systems and their measurements hardened.
By coupling this network architecture with a publish/subscribe messaging protocol, we can guarantee delivery of measurements. In this talk, we will highlight how this messaging protocol is used to securely transfer measurements from sensing systems in the field to a cloud-based long-term storage database. We will also showcase how this same protocol can be used to apply real-time calibration corrections to sensor measurements using previously noted metadata, and how this could be applied to any sensor network.
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