Linux Foundation announced support for Grillo’s Open EEW project in collaboration with IBM to accelerate the standardization and implementation of earthquake early warning (EEW) systems...
Linux Foundation announced support for Grillo’s OpenEEW project in collaboration with IBM to accelerate the standardization and implementation of earthquake early warning (EEW) systems. The project includes Grillo’s EEW solutions that consist of integrated capabilities to detect and analyze earthquakes and to alert communities. OpenEEW was created by Grillo with the support of IBM, USAID, Clinton Foundation, and Arrow Electronics.
An Earthquake Early Warning System (EEW) sends a real-time alert to people before the quake arrives. However, only several institutions have attempted to build solutions because of the incredibly high cost of traditional seismometers, dedicated telecommunications, and custom software.
Grillo has implemented an Internet of Things approach, standardizing a mix of components, software, and know-how to reduce the costs. Since 2017, the Grillo Team has developed and implemented IoT-based systems in Mexico and Chile and has issued public alerts via Twitter, a mobile application, and an alarm device.
“The speed depends on the distance of the earthquake to the user,” said Andres Meira, CEO at Grillo. “Once a sensor detects an earthquake, it is processed in milliseconds and the alert sent to nearby users. If a user is hundreds of kilometers away from the earthquake, they may get one minute or more/less to prepare before they feel shaking. If the earthquake is very close, they may only get a few seconds. Either way, this can be useful, for example, in schools where kids can get beneath a table.”
Earthquakes are vibrations or shifts in the Earth’s crust as a result of tectonic forces that release an amount of energy into an area inside the earth called the hypocentre. The shock causes oscillations that, depending on the intensity, can cause damage to buildings not constructed according to the corresponding regulations.
The earthquake cannot be determined in advance, i.e., knowing with certainty the day and time of the event. However, there is a technology to provide valid support to the population regarding the arrival of the seismic event. In this regard, there are studies already applied in many countries that provide an earthquake warning system to warn the population via smartphones and thus try to reduce damage and casualties.
The warning system provides early warning of expected seismic intensities and time of arrival. These estimates are based on accurate analysis of earthquake magnitude using data observed by seismographs near the epicenter. The warning system aims to mitigate earthquake damage, allowing countermeasures such as slowing down trains, lift control, and allowing people to quickly protect themselves in various environments such as factories, offices, and homes.
The increasing urbanization and especially the strong dependence on the complex infrastructure for telecommunications and transport have led to a careful study of an early warning system for earthquakes by sending warnings to the population. The development of such a system is a fundamental step in reducing the fear of the unknown and the unpredictable nature of earthquakes, while at the same time improving people’s safety (Figure 1).
Early warning is possible because information can be sent through communication systems virtually instantaneously, while seismic waves travel across the Earth at speeds ranging from 1 to 7 km/s (depending on the type of wave P, S, and a half). This means that the agitation can take seconds or even minutes to travel from where the earthquake occurred to the point where there is the greatest concentration of population.
When an earthquake occurs, seismic waves, including compression or longitudinal (P), transverse (S), and surface (R and L) waves, radiate outward from the epicenter. The faster but weaker P wave travels to nearby sensors, generating alarm signals to carry out protection operations before the arrival of the slower but stronger S waves and surface waves.
The ability to properly send the warning before the seismic event requires some important technical solutions:
a network of sensors to have more data to analyze;
a robust and efficient data processing zone;
computer algorithms to quickly estimate the location, time, and map of the event.
Linux Foundation and Grillo
Earthquakes often have the most serious consequences in developing countries, partly due to construction and infrastructure problems. Alert systems provide public alerts in countries such as Mexico, Japan, South Korea, and Taiwan, but nearly three billion people have difficulty accessing them due to cost. OpenEEW wants to help reduce the cost of EEW systems, accelerate their deployment worldwide, and eventually save lives.
The OpenEEW project includes several key components of the IoT: sensor hardware and firmware that can quickly detect and transmit ground movement, real-time sensing systems that can be deployed on various platforms, from a Kubernetes cluster to a Raspberry Pi; and applications that allow users to receive alerts on hardware, wearable devices or mobile applications as quickly as possible. The open-source community aims to help advance seismic technology by contributing to OpenEEW’s three integrated technology capabilities: sensor implementation, earthquake detection, and alarm sending.
“With OpenEEW you can build your own sensors using the schematics we provide (Find out here), or simply buy directly the assembled product,” said Meira. “These sensors feature a modern MEMS accelerometer, which is far lower noise than those found in smartphones. This provides great quality data that is transmitted to the cloud or a private server provided by the user. The sensors also include custom firmware that provides reliability for the transmission and continuous operation. These sensors have been consistently operating in remote areas of Mexico and Chile since 2017 without any maintenance.”
He continued, “The sensors do continuous calibrations in the firmware to remove any offsets to the acceleration values. They also do some simple filtering. In the cloud (or potentially on the edge in new versions of the firmware), the detection system looks for seismic events using different algorithms such as Short Term Average / Long Term Average, as well as combining signals from different sensors to ensure that its not a false positive.”
The system is based on a microcontroller (ESP32), which has sufficient performance to read the accelerometer and stream data, as well as some other functions. “However, we are currently being supported by Arrow, who is providing engineering for a new sensor that does edge computing and cellular transmission with low power,” said Meira. “This will allow for new installation possibilities previously limited by lack of internet or power.”
He continued, “The next stage, in development now, is to use machine learning to improve these detections, potentially using only a single sensor’s readings. We have published all the unprocessed data since 2017 to facilitate this.”
By going with microcontrollers, a new generation of MEMS accelerometers, and cloud computing, it is now feasible to offer these communities a solution that was previously only available in a handful of countries at great public expense. “By offering the detection systems as open source, it is now possible for the software to be deployed on different platforms depending on the need,” said Meira. “This may, for example, run on a local Raspberry Pi (in the case of small networks) or laptop, which can offer latency benefits instead of relying on a cloud service hundreds of kilometers away.”
The alarms or apps that receive the alerts can also be tailored to the user. “In the OpenEEW GitHub, we offer an example app that people can create, but they may also want to channel the alerts to their Twitter feed, public address system, or even a building management system. We are agnostic about how the last mile is achieved.
The OpenEEW sensor features a high-performance MEMS accelerometer and Ethernet or Wi-Fi connectivity. It also includes a loud buzzer and three bright NeoPixel LEDs for alarm functions.
Components are mounted in a PCB with the corresponding circuitry. The board operates at 3.3V with a maximum current of 1A. The accelerometer is accessed via the SPI interface, specifically ESP32’s VSPI. GPS can optionally be added with a UART interface (figure 2).
OpenEEW sensors require specific installation conditions to ensure acceptable data quality. An example of installation is shown in figure 3. The system requires proximity to the router and a good signal-to-noise ratio for optimal packet transmission.
OpenEEW, which was created with support from the U.S. Agency for International Development, the Clinton Foundation, and Arrow Electronics, includes support from the IoT’s core technology.
IBM, which originally supported Grillo through the Clinton Global Initiative (CGI) Action Network of the Clinton Foundation, said it would add OpenEEW technologies to Call for Code, which is supported by the Linux Foundation. Call for Code, which was launched in May 2018, aims to combine data, AI, and blockchain technologies to create systems that better respond to natural disasters.
In addition to this, IBM claims it has developed a new system to display sensor readings and implemented six Grillo sensors to conduct tests in Puerto Rico. With OpenEEW, IBM hopes to encourage EEW construction in places like Nepal, New Zealand, Ecuador, and other seismic regions. These communities could then help OpenEEW by advancing sensor hardware design and creating methods to provide alerts to citizens.
This article was first published on EETimes Europe