Welcome!

IoT User Interface Authors: Roger Strukhoff, Sematext Blog, Pat Romanski, Liz McMillan, Elizabeth White

Related Topics: Microservices Expo, Java IoT, Industrial IoT, Microsoft Cloud, IoT User Interface, Apache

Microservices Expo: Article

Intelligent Complex Event Processing with Artificial Neural Network

Solve highly complex problems in real or near real time

In the current world, data is continuously being generated across various layers of organizations and environment due to changes in the system states or due to the occurrence of new events. These changes in the state of the existing system can happen due to the arrival of a new order request, customer service calls for complaints or feedback, changes in the company stock prices, text or multimedia messages, emails, social media posts, traffic reports, weather reports or any other kind of data. Simply producing reports using these data on a pre-defined schedule is not enough. Decision makers need real-time alerts and intelligent insight of all that is happening within and around the organization so that they may take meaningful reactive and proactive action before it is too late based on the new information being continuously generated.

A powerful technique called Complex Event Processing (CEP) is used for analyzing events coming from multiple sources over a specific period of time by detecting complex patterns between events and by making correlations. Apart from CEP, Artificial Neural Network (ANN) is also used to model complex relationships between input events data. Both the approaches have their own pros and cons. In this article, we tried to describe a use case in the health care domain with the solution architecture using both CEP and ANN, combining the best capabilities of both the approaches. We have shown how one can use both the techniques together to solve highly complex problems in real or near real time.

The following two sections gives brief introduction about CEP and ANN respectively with their key benefits. In section 4, we have explained the approach which combines both the CEP and the ANN efficiently to provide better solution of complex problems. Section 5 and 6 explains the Health Care: Patient Monitoring System use case with the problem description and proposed solution approach using CEP and ANN, followed by the section with summary and conclusion.

Complex Event Processing
Complex event processing is one of the key Operational Intelligence technology used to process one or more stream of data and information (also known as events) and deriving a meaningful conclusion using them. It allows one to set the request for an analysis or some query and then have it continuously executed and evaluated over time against one or many streams of events in a highly efficient manner. CEP is all about processing events that combines data from many sources to infer events or patterns that suggest more complicated circumstances [1].  For example, CEP can be used as Fraud Detection system, to detect suspicious credit card usage by monitoring credit card activity in real time and relating the current transactions with the historical data about a particular customer. The historical data which can be used by CEP Fraud Detection system can be an average transaction amount, minimum and maximum values of the previous transactions, transaction frequencies, locality etc. On detecting fraudulent activity, CEP system can send an alert via an SMS or email to the customer or the credit card service provider to take quick reaction.

The primary goal of CEP is to (1) detect meaningful events or pattern of events which signifies either threats or opportunities from the series of events being received continuously and (2) send alerts for the same to responsible entity to respond as quickly as possible. The following diagram (as figure-1) describes high level view of the CEP system.

Figure 1: High-level view of the CEP system

As shown in Figure 1, the core of the complex event processing system is made up of set of input adapters, set of output adapters and various event processing modules such as event filtering modules, in-memory caching, aggregation over different windows (time-window, sliding window, tumbling window etc.), database lookups module, database writes module, correlation, joins, event pattern matching, state machines, dynamic queries etc. More the number of I/O adapters supported by the CEP, more flexible and adaptable it is and will be able to cover wide range of use cases as compared to the CEP tool having support for limited set of I/O adapters.

Key Benefits of CEP
The following are some of the key benefits the CEP provides to the business.

  • Automatically identifies rare but important relationships between seemingly unrelated events or stream of events and accelerate timely responses to both the threats and opportunities.
  • Using sophisticated analysis and event pattern matching techniques, the CEP improves resource allocation and timely problem resolution by prioritize situations that require the most urgent attention in real or near real time based on arrival of events.
  • CEP helps organization to reduce operating costs by monitoring end-to-end performance of the system and provide timely alerts to rapidly identify potential SLA violations.
  • CEP helps organization to fine tune their business processes by correlating SLA performance with industry metrics e.g. Six Sigma and various Quality metrics, to enhance overall productivity.

Artificial Neural Network
An Artificial Neural Network (ANN) is a computational model which resembles with the way human brain is made up of in structure and the way it works. Similar to human brain which is made up of billions of neurons interconnected by synapses, the ANN can be form as a network of computational nodes connected with each other through links. The ANN needs to be trained repeatedly with specific set of training data before it can be used in production environment. Due to its adaptive nature, the internal structure of the ANN can easily be changed based on external or internal information that flows through the network during the learning phase [2]. The links are assigned weights during training process, which regulate the flow of data from one node to another. ANNs are used to model complex relationships between inputs and outputs data. ANN can efficiently find various patterns in input data or to predict future values of the system parameters. Due to its flexible construct, ANN can be very helpful in modeling complex systems which are very difficult otherwise by using traditional modeling techniques. Artificial neural networks are being applied in diverse of domains and fields. They are extensively used for doing image processing and recognition, speech recognition, credit card fraud detection, for prediction of protein structure in biotechnology and in the field of genetic science.

Artificial neural network consists of two types of interfaces with the external world, the input and the output. Since the ANN is made up of nodes or neurons and the links between them, a subset of total nodes in the ANN act as input nodes, which take data from the external world, a subset of nodes act as output node, which produces result and zero or more hidden nodes act as intermediary nodes, with having only connections with input or output nodes or other hidden nodes.  Hence, the ANN is made up of nodes in input layer, nodes in output layer and zero or more internal layers.

Figure 2: High-level view of artificial neural network

The high level view of ANN is shown in figure-2. The diagram shows a typical neural network with total 12 nodes, three nodes in the input layer, seven nodes in the hidden layer and two nodes in the output layer. Before the neural network can be used in actual production environment, it is needed to be trained for particular environment. The process of training of ANN is called learning of neural network, which is generally done in one of the following three ways:  (a) supervised learning; (b) unsupervised learning and (c) reinforcement learning. The more details about the ANN learning can be found in [2].

Key Benefits of ANN
Since ANNs can infer a function from inputs, they particularly are used in the applications where the complexity of the input data or system modeling makes the design of such a function impractical using traditional approaches. Following are some of the key benefits ANN provides.

  • It is very easy to apply ANN to problem domains where the relationships are quite dynamic or non-linear among the input and output.
  • Since ANN is capable of capturing many kind of relationships and complex patterns among data, ANN allows user to easily model the system which otherwise is very difficult or impossible to represent through traditional modeling approaches.
  • The training information is not stored in any single element but is distributed in the entire network structure. This makes ANN fault tolerant and it reduces the impact of erroneous input on the result.

CEP and ANN Together
Having seen the key properties and benefits of using both, CEP and ANN, this section describes what if one apply both together for specific set of problems to make the modeling of the system and solution easy and efficient. The CEP is best in accepting data or events from multiple channels and apply various event processing operations on it, such as event filtering, event pattern matching, aggregation etc. Apart from that user can configure alerts based on various thresholds on various system parameters. But the CEP tools lakes the ability to predict future events or determine the values of the system parameters for future events, which can be efficiently done by the ANN. So if we combine best of CEP and best of ANN for a particular problem, the resulting solution could be very effective and efficient. In the following sections, we have described how the CEP and the ANN can be used together to solve a particular problem of patient monitoring system in the domain of Health care and medicines.

Patient Monitoring System
The patient monitoring system monitors and keeps track of various body parameters of the patient and provides the data for analysis to monitoring system. Various body parameters could be blood pressure, the percentage of oxygen in the blood, glucose level in the blood, heart beat rate, change in body temperature etc. Data provided by the patient monitoring system helps to make diagnostic decisions easy and more reliable. The quality of patient treatment and care giving can greatly be improved with the use of patient monitoring systems, since it allows generating alerts in case of sudden changes in the patient body parameters which could be dangerous to the patient's health or could be life threatening some time [3].

A Use Case
Goals of the patient monitoring system are to (1) continuously keeps track of the patient's body parameters and store the data for present or future references, (2) identify life-threatening changes in patient's body and raises timely alarms for the same, and (3) to determine whether patient's health is in normal condition or it is improving or worsening based on the continuously arriving input data from various medical monitors. Since no two human bodies react in a same way against given situation or medication, it is very difficult to derived common rule set which can be applied to all human bodies. Similarly, one person's body also reacts differently in different medical and environmental situations. For example, a particular heart beat rate can be normal in some situation, while the same can be very abnormal in the other situation. So to judge the proper health condition, a trained professional is required, i.e. a specialist doctor, who studies all the observations and determine the correct state of patient's health. If the patient monitoring system is equipped with some intelligent agent who will use patient's medical history and current body parameters observations, then quality of patient care delivery can greatly be improved. We combine CEP and ANN together to propose system architecture which tries to act as an intelligent agent of the patient monitoring system, which is described in the following section.

System Architecture of the intelligent patient monitoring system using CEP and ANN
The following diagram, in Figure 3, shows the architecture of the intelligent patient monitoring system using CEP and ANN. There are total five key components; (1) Medical monitors, (2) CEP, (3) Patient's medical history and diagnosis data store, (4) ANN and (5) ANN output to action message converter.

(1) Medical Monitors
Medical monitors are medical devices used for monitoring patient's body parameters. It can consist of one or more body parameter sensors, processing components, display devices as well as communication links for displaying, recording or transmitting data or results elsewhere through a monitoring network. In the proposed architecture, the data generated by medical monitors are fed into the CEP system. [3]

Figure 3: Architecture of the intelligent patient monitoring system using CEP and ANN

The CEP section of the proposed architecture is one of the key components of the system. It receives all the monitored data and applies various event processing techniques, such as filtering, aggregation etc. over input event streams and provides the data for further processing to ANN module. Various input adapters available in CEP make it possible to collect data from different types of sensors or monitors and process them collectively. In CEP module, various event processing rule are written specific to the patient.

(3) Patient's medical history and diagnosis data store
This is the data store where patient's medical history and diagnosis data is stored. It could be traditional RDBMS storage system. The data stored in this storage are used for ANN training purpose. The new data is continuously added into the same data storage and will be used next time when ANN will be trained again with patient's latest medical and diagnosis data.

(4) ANN
The ANN model for the patient is computational neural network specific to the patient and trained using patient's all medical and diagnosis data. This trained ANN model is used for real-time diagnosis and care delivery. The decision is taken based on the input data coming from the CEP output adapters. The patient specific ANN model is trained at regular interval may be daily or on need bases. These regular updates which include latest knowledge about measured body parameters, diagnosis and medication information of the patient, helps ANN model to make accurate predictions. It is also possible to make ANN take biased decision by giving more weight to either historical data or the latest data during training. All these make ANN the most critical component of the system.

(5) ANN output to action message converter
The output generated by the ANN is generally real numbers and they are needed to be mapped to the meaningful information so that appropriate action can be taken. This is done by the ANN output to action message converter. The module not only map ANN output to real world information but it can also sends action data or alerts to devices or human being through email, SMS, alarm system etc. The threshold for various alerts can be configured so it can adapt to the changes happening to the health and body.

Together all these components make a very flexible, intelligent and efficient patient monitoring system. The proposed architecture shows how one can use CEP and ANN together more effectively to model the complex problem and provide efficient solution alternative over the traditional approaches.

Conclusion
Complex event processing and artificial neural network are the two widely used solution techniques for the problems that are very difficult to model using traditional approaches. In this article, we have described both the approaches in brief with their key capabilities. We have also described a use case for intelligent patient monitoring system with the solution architecture using both CEP and ANN and combining the best capabilities of both the approaches. We have shown how one can use both the techniques together to solve highly complex problems in real or near real time.

References

  1. Complex event processing, http://en.wikipedia.org/wiki/Complex_event_processing#cite_note-1
  2. Artificial neural network, http://en.wikipedia.org/wiki/Artificial_neural_network
  3. Patient Monitoring Systems - Part 1, http://www.philblock.info/hitkb/p/patient_monitoring_systems.html

More Stories By Kamalkumar Mistry

Kamalkumar Mistry is a Technology Analyst at Infosys Limited, Pune, India. At Infosys, he is part of a research group called Infosys Labs (http://www.infosys.com/infosys-labs).

Comments (0)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.


@CloudExpo Stories
Complete Internet of Things (IoT) embedded device security is not just about the device but involves the entire product’s identity, data and control integrity, and services traversing the cloud. A device can no longer be looked at as an island; it is a part of a system. In fact, given the cross-domain interactions enabled by IoT it could be a part of many systems. Also, depending on where the device is deployed, for example, in the office building versus a factory floor or oil field, security ha...
More and more companies are looking to microservices as an architectural pattern for breaking apart applications into more manageable pieces so that agile teams can deliver new features quicker and more effectively. What this pattern has done more than anything to date is spark organizational transformations, setting the foundation for future application development. In practice, however, there are a number of considerations to make that go beyond simply “build, ship, and run,” which changes ho...
SYS-CON Events announced today that Niagara Networks will exhibit at the 19th International Cloud Expo, which will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. Niagara Networks offers the highest port-density systems, and the most complete Next-Generation Network Visibility systems including Network Packet Brokers, Bypass Switches, and Network TAPs.
Using new techniques of information modeling, indexing, and processing, new cloud-based systems can support cloud-based workloads previously not possible for high-throughput insurance, banking, and case-based applications. In his session at 18th Cloud Expo, John Newton, CTO, Founder and Chairman of Alfresco, described how to scale cloud-based content management repositories to store, manage, and retrieve billions of documents and related information with fast and linear scalability. He addres...
SYS-CON Events announced today that eCube Systems, a leading provider of middleware modernization, integration, and management solutions, will exhibit at @DevOpsSummit at 19th International Cloud Expo, which will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. eCube Systems offers a family of middleware evolution products and services that maximize return on technology investment by leveraging existing technical equity to meet evolving business needs. ...
SYS-CON Events announced today that Commvault, a global leader in enterprise data protection and information management, has been named “Bronze Sponsor” of SYS-CON's 19th International Cloud Expo, which will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. Commvault is a leading provider of data protection and information management solutions, helping companies worldwide activate their data to drive more value and business insight and to transform moder...
The many IoT deployments around the world are busy integrating smart devices and sensors into their enterprise IT infrastructures. Yet all of this technology – and there are an amazing number of choices – is of no use without the software to gather, communicate, and analyze the new data flows. Without software, there is no IT. In this power panel at @ThingsExpo, moderated by Conference Chair Roger Strukhoff, panelists will look at the protocols that communicate data and the emerging data analy...
Digital innovation is the next big wave of business transformation based on digital technologies of which IoT and Big Data are key components, For example: Business boundary innovation is a challenge to excavate third-party business value using IoT and BigData, like Nest Business structure innovation may propose re-building business structure from scratch, as Uber does in the taxicab industry The social model innovation is also a big challenge to the new social architecture with the design fr...
Fifty billion connected devices and still no winning protocols standards. HTTP, WebSockets, MQTT, and CoAP seem to be leading in the IoT protocol race at the moment but many more protocols are getting introduced on a regular basis. Each protocol has its pros and cons depending on the nature of the communications. Does there really need to be only one protocol to rule them all? Of course not. In his session at @ThingsExpo, Chris Matthieu, co-founder and CTO of Octoblu, walk you through how Oct...
We’ve been doing it for years, decades for some. How many websites have you created accounts on? Your bank, your credit card companies, social media sites, hotels and travel sites, online shopping sites, and that’s just the start. We do it often without even thinking about it, quickly entering our personal information, our data, in a plethora of systems. Sometimes we’re not even aware of the information we are providing. It could be very personal information (think of the security questions you ...
Is your aging software platform suffering from technical debt while the market changes and demands new solutions at a faster clip? It’s a bold move, but you might consider walking away from your core platform and starting fresh. ReadyTalk did exactly that. In his General Session at 19th Cloud Expo, Michael Chambliss, Head of Engineering at ReadyTalk, will discuss why and how ReadyTalk diverted from healthy revenue and over a decade of audio conferencing product development to start an innovati...
All clouds are not equal. To succeed in a DevOps context, organizations should plan to develop/deploy apps across a choice of on-premise and public clouds simultaneously depending on the business needs. This is where the concept of the Lean Cloud comes in - resting on the idea that you often need to relocate your app modules over their life cycles for both innovation and operational efficiency in the cloud. In his session at @DevOpsSummit at19th Cloud Expo, Valentin (Val) Bercovici, CTO of So...
Data is an unusual currency; it is not restricted by the same transactional limitations as money or people. In fact, the more that you leverage your data across multiple business use cases, the more valuable it becomes to the organization. And the same can be said about the organization’s analytics. In his session at 19th Cloud Expo, Bill Schmarzo, CTO for the Big Data Practice at EMC, will introduce a methodology for capturing, enriching and sharing data (and analytics) across the organizati...
IoT is fundamentally transforming the auto industry, turning the vehicle into a hub for connected services, including safety, infotainment and usage-based insurance. Auto manufacturers – and businesses across all verticals – have built an entire ecosystem around the Connected Car, creating new customer touch points and revenue streams. In his session at @ThingsExpo, Macario Namie, Head of IoT Strategy at Cisco Jasper, will share real-world examples of how IoT transforms the car from a static p...
SYS-CON Events announced today that Tintri Inc., a leading producer of VM-aware storage (VAS) for virtualization and cloud environments, will exhibit at the 19th International Cloud Expo, which will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. Tintri VM-aware storage is the simplest for virtualized applications and cloud. Organizations including GE, Toyota, United Healthcare, NASA and 6 of the Fortune 15 have said “No to LUNs.” With Tintri they mana...
There is little doubt that Big Data solutions will have an increasing role in the Enterprise IT mainstream over time. Big Data at Cloud Expo - to be held November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA - has announced its Call for Papers is open. Cloud computing is being adopted in one form or another by 94% of enterprises today. Tens of billions of new devices are being connected to The Internet of Things. And Big Data is driving this bus. An exponential increase is...
Whether they’re located in a public, private, or hybrid cloud environment, cloud technologies are constantly evolving. While the innovation is exciting, the end mission of delivering business value and rapidly producing incremental product features is paramount. In his session at @DevOpsSummit at 19th Cloud Expo, Kiran Chitturi, CTO Architect at Sungard AS, will discuss DevOps culture, its evolution of frameworks and technologies, and how it is achieving maturity. He will also cover various st...
Creating replica copies to tolerate a certain number of failures is easy, but very expensive at cloud-scale. Conventional RAID has lower overhead, but it is limited in the number of failures it can tolerate. And the management is like herding cats (overseeing capacity, rebuilds, migrations, and degraded performance). Download Slide Deck: ▸ Here In his general session at 18th Cloud Expo, Scott Cleland, Senior Director of Product Marketing for the HGST Cloud Infrastructure Business Unit, discusse...
If you had a chance to enter on the ground level of the largest e-commerce market in the world – would you? China is the world’s most populated country with the second largest economy and the world’s fastest growing market. It is estimated that by 2018 the Chinese market will be reaching over $30 billion in gaming revenue alone. Admittedly for a foreign company, doing business in China can be challenging. Often changing laws, administrative regulations and the often inscrutable Chinese Interne...
Internet of @ThingsExpo, taking place November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA, is co-located with the 19th International Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world and ThingsExpo Silicon Valley Call for Papers is now open.