IoT Sensing and the Importance of a Time-Series Database
The chief technology officers from InfluxData and Worldsensing discuss their role in monitoring the Ponte Vecchio bridge, the evolution of IoT and other topics.
When a sinkhole opened up near the Ponte Vecchio bridge in Florence, Italy in 2016, authorities worried the famed structure could be at risk. The industrial IoT company Worldsensing stepped in to enlist the help of the InfluxData to help monitor the bridge. Working in partnership with the University of Florence and the Municipality of Florence, Worldsensing used wireless sensors to determine the bridge was safe, while on the backend, Worldsensing used a time-series database from InfluxData to look for anomalies in the sensor data.
The Barcelona-headquartered company Worldsensing began using InfluxDB, an open-source time-series database, for an unrelated application — to help monitor the performance of its server infrastructure. After its technical staff deemed it to fit their internal requirements, the scope of applications increased. “In the end, our customers also needed tools to analyze their time-series data,” said Albert Zaragoza, chief technology officer at Worldsensing in an interview at IoT Solutions World Congress.
[IoT World is North America’s largest IoT event where strategists, technologists and implementers connect, putting IoT, AI, 5G and Edge into action across industry verticals. Book your ticket now.]
While the leaders of InfluxData don’t tend to be directly involved with IIoT projects, they have long seen the utility in their time-series database for IoT applications. “One of the key insights I had when I started [InfluxData] company was: ‘Time series is a useful abstraction for solving problems in sensor data, industrial IoT, consumer-grade IoT, server monitoring, application performance monitoring, real-time analytics and all of these different things,” said Paul Dix, chief technology officer at InfluxData.
The partnership between Worldsensing and InfluxData represents a typical pattern for industrial IoT applications. Because of the sheer complexity, IIoT vendors frequently must draw from a variety of hardware and software tools to help clients address a given problem.
In the following Q&A, we explore the partnership between the two companies, touching on their role in helping secure the Ponte Vecchio bridge, the current state of the IIoT market, and the current shortage of data science and machine learning experts.
Albert, can you tell me about your company’s core focus and how your company got involved in the Ponte Vecchio project?
Albert: Basically, we help digitize mines, industrial infrastructures and cities. In the Ponte Vecchio example, they wanted to make sure that the bridge didn’t fall on account of the sinkhole.
We provided geological sensors and IoT data loggers connected to a gateway that ingests data from those sensors. The system sends the sensor data to an office, where they analyze the data. There are geotechnical experts there who analyze that data.
In some of the use cases, we use Influx to analyze time-series events. In IoT, many events are time series related. Depending on the use case and the customer, sensors might send data, say, every 30 seconds or once per minute. In the end, it’s all about logging time series data.
