|By Kamalkumar Mistry||
|November 29, 2012 11:00 AM EST||
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 . 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 . 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 .
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 .
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. 
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.
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.
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.
- Complex event processing, http://en.wikipedia.org/wiki/Complex_event_processing#cite_note-1
- Artificial neural network, http://en.wikipedia.org/wiki/Artificial_neural_network
- Patient Monitoring Systems - Part 1, http://www.philblock.info/hitkb/p/patient_monitoring_systems.html
When it comes to IoT in the enterprise, namely the commercial building and hospitality markets, a benefit not getting the attention it deserves is energy efficiency, and IoT’s direct impact on a cleaner, greener environment when installed in smart buildings. Until now clean technology was offered piecemeal and led with point solutions that require significant systems integration to orchestrate and deploy. There didn't exist a 'top down' approach that can manage and monitor the way a Smart Building actually breathes - immediately flagging overheating in a closet or over cooling in unoccupied ho...
Oct. 5, 2015 11:45 PM EDT Reads: 178
In his session at @ThingsExpo, Tony Shan, Chief Architect at CTS, will explore the synergy of Big Data and IoT. First he will take a closer look at the Internet of Things and Big Data individually, in terms of what, which, why, where, when, who, how and how much. Then he will explore the relationship between IoT and Big Data. Specifically, he will drill down to how the 4Vs aspects intersect with IoT: Volume, Variety, Velocity and Value. In turn, Tony will analyze how the key components of IoT influence Big Data: Device, Connectivity, Context, and Intelligence. He will dive deep to the matrix...
Oct. 5, 2015 11:00 PM EDT Reads: 214
SYS-CON Events announced today that IBM Cloud Data Services has been named “Bronze Sponsor” of SYS-CON's 17th Cloud Expo, which will take place on November 3–5, 2015, at the Santa Clara Convention Center in Santa Clara, CA. IBM Cloud Data Services offers a portfolio of integrated, best-of-breed cloud data services for developers focused on mobile computing and analytics use cases.
Oct. 5, 2015 11:00 PM EDT Reads: 601
The enterprise is being consumerized, and the consumer is being enterprised. Moore's Law does not matter anymore, the future belongs to business virtualization powered by invisible service architecture, powered by hyperscale and hyperconvergence, and facilitated by vertical streaming and horizontal scaling and consolidation. Both buyers and sellers want instant results, and from paperwork to paperless to mindless is the ultimate goal for any seamless transaction. The sweetest sweet spot in innovation is automation. The most painful pain point for any business is the mismatch between supplies a...
Oct. 5, 2015 03:30 PM EDT Reads: 115
Mobile messaging has been a popular communication channel for more than 20 years. Finnish engineer Matti Makkonen invented the idea for SMS (Short Message Service) in 1984, making his vision a reality on December 3, 1992 by sending the first message ("Happy Christmas") from a PC to a cell phone. Since then, the technology has evolved immensely, from both a technology standpoint, and in our everyday uses for it. Originally used for person-to-person (P2P) communication, i.e., Sally sends a text message to Betty – mobile messaging now offers tremendous value to businesses for customer and empl...
Oct. 5, 2015 01:15 PM EDT Reads: 157
SYS-CON Events announced today that ProfitBricks, the provider of painless cloud infrastructure, will exhibit at SYS-CON's 17th International Cloud Expo®, which will take place on November 3–5, 2015, at the Santa Clara Convention Center in Santa Clara, CA. ProfitBricks is the IaaS provider that offers a painless cloud experience for all IT users, with no learning curve. ProfitBricks boasts flexible cloud servers and networking, an integrated Data Center Designer tool for visual control over the cloud and the best price/performance value available. ProfitBricks was named one of the coolest Clo...
Oct. 5, 2015 01:00 PM EDT Reads: 719
“The Internet of Things transforms the way organizations leverage machine data and gain insights from it,” noted Splunk’s CTO Snehal Antani, as Splunk announced accelerated momentum in Industrial Data and the IoT. The trend is driven by Splunk’s continued investment in its products and partner ecosystem as well as the creativity of customers and the flexibility to deploy Splunk IoT solutions as software, cloud services or in a hybrid environment. Customers are using Splunk® solutions to collect and correlate data from control systems, sensors, mobile devices and IT systems for a variety of Ind...
Oct. 5, 2015 12:00 PM EDT Reads: 572
Organizations already struggle with the simple collection of data resulting from the proliferation of IoT, lacking the right infrastructure to manage it. They can't only rely on the cloud to collect and utilize this data because many applications still require dedicated infrastructure for security, redundancy, performance, etc. In his session at 17th Cloud Expo, Emil Sayegh, CEO of Codero Hosting, will discuss how in order to resolve the inherent issues, companies need to combine dedicated and cloud solutions through hybrid hosting – a sustainable solution for the data required to manage I...
Oct. 5, 2015 12:00 PM EDT Reads: 415
You have your devices and your data, but what about the rest of your Internet of Things story? Two popular classes of technologies that nicely handle the Big Data analytics for Internet of Things are Apache Hadoop and NoSQL. Hadoop is designed for parallelizing analytical work across many servers and is ideal for the massive data volumes you create with IoT devices. NoSQL databases such as Apache HBase are ideal for storing and retrieving IoT data as “time series data.”
Oct. 5, 2015 11:45 AM EDT Reads: 444
Clearly the way forward is to move to cloud be it bare metal, VMs or containers. One aspect of the current public clouds that is slowing this cloud migration is cloud lock-in. Every cloud vendor is trying to make it very difficult to move out once a customer has chosen their cloud. In his session at 17th Cloud Expo, Naveen Nimmu, CEO of Clouber, Inc., will advocate that making the inter-cloud migration as simple as changing airlines would help the entire industry to quickly adopt the cloud without worrying about any lock-in fears. In fact by having standard APIs for IaaS would help PaaS expl...
Oct. 5, 2015 11:30 AM EDT Reads: 430
As more and more data is generated from a variety of connected devices, the need to get insights from this data and predict future behavior and trends is increasingly essential for businesses. Real-time stream processing is needed in a variety of different industries such as Manufacturing, Oil and Gas, Automobile, Finance, Online Retail, Smart Grids, and Healthcare. Azure Stream Analytics is a fully managed distributed stream computation service that provides low latency, scalable processing of streaming data in the cloud with an enterprise grade SLA. It features built-in integration with Azur...
Oct. 5, 2015 10:00 AM EDT Reads: 726
Apps and devices shouldn't stop working when there's limited or no network connectivity. Learn how to bring data stored in a cloud database to the edge of the network (and back again) whenever an Internet connection is available. In his session at 17th Cloud Expo, Bradley Holt, Developer Advocate at IBM Cloud Data Services, will demonstrate techniques for replicating cloud databases with devices in order to build offline-first mobile or Internet of Things (IoT) apps that can provide a better, faster user experience, both offline and online. The focus of this talk will be on IBM Cloudant, Apa...
Oct. 5, 2015 09:45 AM EDT Reads: 435
SYS-CON Events announced today that HPM Networks will exhibit at the 17th International Cloud Expo®, which will take place on November 3–5, 2015, at the Santa Clara Convention Center in Santa Clara, CA. For 20 years, HPM Networks has been integrating technology solutions that solve complex business challenges. HPM Networks has designed solutions for both SMB and enterprise customers throughout the San Francisco Bay Area.
Oct. 5, 2015 09:00 AM EDT Reads: 562
As enterprises capture more and more data of all types – structured, semi-structured, and unstructured – data discovery requirements for business intelligence (BI), Big Data, and predictive analytics initiatives grow more complex. A company’s ability to become data-driven and compete on analytics depends on the speed with which it can provision their analytics applications with all relevant information. The task of finding data has traditionally resided with IT, but now organizations increasingly turn towards data source discovery tools to find the right data, in context, for business users, d...
Oct. 5, 2015 08:00 AM EDT Reads: 376
SYS-CON Events announced today that MobiDev, a software development company, will exhibit at the 17th International Cloud Expo®, which will take place November 3-5, 2015, at the Santa Clara Convention Center in Santa Clara, CA. MobiDev is a software development company with representative offices in Atlanta (US), Sheffield (UK) and Würzburg (Germany); and development centers in Ukraine. Since 2009 it has grown from a small group of passionate engineers and business managers to a full-scale mobile software company with over 150 developers, designers, quality assurance engineers, project manage...
Oct. 5, 2015 05:00 AM EDT Reads: 722
The broad selection of hardware, the rapid evolution of operating systems and the time-to-market for mobile apps has been so rapid that new challenges for developers and engineers arise every day. Security, testing, hosting, and other metrics have to be considered through the process. In his session at Big Data Expo, Walter Maguire, Chief Field Technologist, HP Big Data Group, at Hewlett-Packard, will discuss the challenges faced by developers and a composite Big Data applications builder, focusing on how to help solve the problems that developers are continuously battling.
Oct. 5, 2015 04:00 AM EDT Reads: 400
Learn how IoT, cloud, social networks and last but not least, humans, can be integrated into a seamless integration of cooperative organisms both cybernetic and biological. This has been enabled by recent advances in IoT device capabilities, messaging frameworks, presence and collaboration services, where devices can share information and make independent and human assisted decisions based upon social status from other entities. In his session at @ThingsExpo, Michael Heydt, founder of Seamless Thingies, will discuss and demonstrate how devices and humans can be integrated from a simple clust...
Oct. 4, 2015 12:00 PM EDT Reads: 621
SYS-CON Events announced today that Cloud Raxak has been named “Media & Session Sponsor” of SYS-CON's 17th Cloud Expo, which will take place on November 3–5, 2015, at the Santa Clara Convention Center in Santa Clara, CA. Raxak Protect automates security compliance across private and public clouds. Using the SaaS tool or managed service, developers can deploy cloud apps quickly, cost-effectively, and without error.
Oct. 3, 2015 01:15 PM EDT Reads: 581
Who are you? How do you introduce yourself? Do you use a name, or do you greet a friend by the last four digits of his social security number? Assuming you don’t, why are we content to associate our identity with 10 random digits assigned by our phone company? Identity is an issue that affects everyone, but as individuals we don’t spend a lot of time thinking about it. In his session at @ThingsExpo, Ben Klang, Founder & President of Mojo Lingo, will discuss the impact of technology on identity. Should we federate, or not? How should identity be secured? Who owns the identity? How is identity ...
Oct. 3, 2015 11:00 AM EDT Reads: 415
SYS-CON Events announced today that Solgeniakhela will exhibit at SYS-CON's 17th International Cloud Expo®, which will take place on November 3–5, 2015, at the Santa Clara Convention Center in Santa Clara, CA. Solgeniakhela is the global market leader in Cloud Collaboration and Cloud Infrastructure software solutions. Designed to “Bridge the Gap” between Personal and Professional Social, Mobile and Cloud user experiences, our solutions help large and medium-sized organizations dramatically improve productivity, reduce collaboration costs, and increase the overall enterprise value by bringing ...
Oct. 2, 2015 10:00 PM EDT Reads: 549