What is Real-Time Alerting?

What is Real-Time Alerting?

Real-time alerting can be understood as both a concept and a loose set of rules within the field of analytics. Real-time alerting provides continuous updates on trends and changes in monitored resources, whether within the actual software or in a system operated by software. Typically, the power of real-time alerting is achieved by creating systems or software components that continually monitor a resource (such as a camera, a sensor, or a field in a database). The real-time aspect is of utmost importance when technicians and developers are creating a new system, testing an existing one, or using it in the field, and require second-by-second trend reporting of critical data.

Benefits of Real-Time Alerting

Fast reaction

Real-time alerting, as a concept in analytic software design, provides significant value across numerous applications and industries worldwide. From automotive telematics (the remote monitoring and communication protocols for vehicles and other relevant assets) to financial markets, to smart factories and Industry 4.0 applications, the ability to receive and respond to events as they occur is of the highest importance.

Real-time alerting is related to event-driven logic. The two concepts are often used together, but the relation can be as simple as:

• a quick message (whether an error or other alert)
• as a notification that a certain condition has changed, or
• a needle or other indicator moving on a digital dial.

Leveraging Event-driven Logic

Event-driven logic, the logical structure of software that provides immediate and definite responses to changes in the status of a resource, is currently one of the best solutions for rapidly reacting to changed conditions communicated by real-time alerting. Event-driven logic is flexible enough to be used across a wide range of situations because its input and response typologies are varied. For this reason, in many applications, when real-time alerting is needed, event-driven logic is a method programmers and developers choose to implement it.

Implementation

Developers have access to multiple software suites custom-tailored to specific applications for providing real-time alerts. Conversely, they can create or insert software components into existing software to provide real-time alerting functionality, depending on the application's requirements. The ways in which real-time alerting can be implemented are nearly as varied as the situations and solutions to which this concept applies. However, regardless of how it is integrated into a system or software, real-time alerting does very well at providing nearly instantaneous responses and tracking changes and trends across a vast range of industrial and academic applications worldwide.

These benefits easily translate into applications as diverse as timing, scoring, and analyzing athletic events, instantaneous monitoring of a patient’s vital signs in healthcare settings, and keeping a rocket on its optimal flight path. In the automotive realm, real-time alerting is widely used; Software-Defined Vehicles (SDVs) depend on it for everything from providing tactile steering feedback to a driver to rerouting that driver’s morning commute based on satellite information to communicating tire pressure warning messages. Real-time alerting, integrated with (sometimes multiple) additional systems, enables and improves products across a wide spectrum of industries.

Functional Elements of Real-Time Alerting

Fast communication

Real-time alerting gives the earliest possible notifications of high-impact events to operators, technicians, developers, and organizations, depending on application and need. These applications might include cybersecurity threat assessment, monitoring, gauges for engine, motor, or battery temperature, or security system sensors.

Alerts versus alarms

While “real-time” certainly should be taken to mean as close to the actual instant as possible (within milliseconds), an “alert” is not always necessarily an “alarm.” When we say “alerting,” we are not speaking only of a response to trouble or unwanted distractions. Real-time alerting is widely used in alarm systems and to notify machinery operators (including drivers of software-defined vehicles) that the system has detected trouble of some kind. However, real-time alerting also works well for messages of status changes within systems, of either “good” or “bad” news, or for simply sending constant operational updates.

Functional elements

Typical real-time monitoring components or systems might include functional elements such as:

• Continuous monitoring, and an infrastructure capable of supporting the constant collection and processing of massive quantities of data: Real-time alerting cannot respond to a function or component that is not under monitoring, and constant monitoring is the only way to ensure that every change (or logically-defined “event”) is noted and logged in real time.
• The allocation of resources or the decision of which inputs to monitor may also be affected by customer or design requirements. Architecture for monitoring components typically includes the monitoring software tools themselves, their data pipelines and input devices, and processing engines that use event-driven logic.
• Immediate detection: For real-time alerting to operate effectively, there can be no delays in detecting valid events, or as few as possible. In industries or applications where milliseconds are vital commodities, a real-time alert system must be perfectly engineered for absolute rapidity and accuracy. If there are unavoidable delays, even for as little as a millisecond, they must be accounted for.
• Threshold-based triggers: Monitored data that crosses a predefined threshold triggers an event that launches the alert. Trigger events can be a simple absolute value, a trend or pattern, or another value set in the monitoring component.
• Automated notification: This can take many forms. As real-time alerting systems are inherently scalable and flexible, they are integrated, whether partially or fully, into thousands of applications we observe and use every day. For example, a digital tachometer dial shows motor speed as revolutions per minute. However, that tach updates the needle’s position on its dial several times per second. The real-time alerting software components on the Electronic Control Unit (ECU) for that device might send readings to that display based on either motor speed changes or elapsed time thresholds. Should that same motor enter an over-speed condition, another threshold would be crossed, prompting the ECU to send a dreaded “redline” alert message.
• Customizable alerts: As in the tachometer instance above, multiple input streams, thresholds, and threshold types can be simultaneously and continuously monitored by real-time alerting systems. Thus, the alerts they produce must also be customizable to fit customer needs for each situation, instance, and asset—for example, allowing a speedometer display to switch from miles per hour to kilometers per hour. This involves the same sensor outputs and the same data processing and communication speeds, but the data are displayed differently.

Iterative improvement

In addition to basic functional elements, real-time alerting systems may include integrated iterative improvement loops. These feedback loops analyze data from the system’s history to identify missed signals, false positives, and other issues, and set up processes to iteratively clarify the system’s alerting rules, improving its performance over time. In addition, depending on the application, real-time alerting systems may be integrated with additional incident resolution or management software. These can include more complex alert messaging, tools for analysis and incident response workflow, or artificial intelligence (AI) modules for option sorting and decision-making.

Real-Time Alerting Practices and Usage

Real-time alerting can be found throughout the broad spectrum of analytics software applications, including:

• Data collection and alert generation,
• Real-time analysis of streaming data, and
• Visualization for decision and planning.

LHP Analytics & IoT builds custom solutions for organizations across a wide range of industries. The solutions our customers require are, much like the organizations, quite disparate from one another and require a custom approach tailored to each use case.

For a full digital or Industry 4.0 transformation of an organization or its operations, we heavily leverage the continuous monitoring, customizable thresholds, and rule-based detection aspects of real-time alerting.

These aspects help us:

• Automate an organization’s engineering processes and optimize workflow, and
• Upgrade to connected warehouses and smart factories with digital twinning, connected products, and full asset identification and monitoring.

These cases typically benefit from analytics integration for deeper insights into the operation of the entire new digital system.

When LHP builds a telematics solution, whether in an automotive context or as a component of an automated factory or other smart resource, we rely on real-time alerting to monitor and report nearly every aspect of the whole project. If we speak only of automotive solutions for a moment (given that modern software-defined vehicles are a rich source of examples), there can be many ECUs actively monitoring, sending information, logging events, and generating data. The telematics system must monitor, differentiate, analyze, and send reports or alerts on input from all the various ECUs in the vehicle to not only optimize the balance between propulsion power and efficiency and fuel or charge consumption, but also to factor in location, route deviation, and thousands of other parameters. Telematics can also encompass machine learning and predictive route forecasting, an important aspect that will become increasingly important as manufacturers continue working to perfect their Advanced Driver Assistance Systems (ADAS) and autonomous driving technology.

Summary

Real-time alerting, especially coupled with the power of event-driven logic and architecture, is a crucial element in modern data operations, monitoring, and analysis. Information can come from cameras, sensors, or any of a vast array of automotive electronic control units. One major strength of real-time alerting is that it can be implemented in many ways, from automotive traction control to remote tool breakage notifications in a smart factory. Real-time alerting can be utilized to monitor and analyze resources, conditions, and events, and is a major tool the LHP Analytics and IoT team uses for data management, analysis, and complex event processing in smart and connected applications for customers across multiple industries.