Building the Internet of Things
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c.System processing costAn IoT system with only the ability to ingest and offload data combined with the ability to send commands is not complete. This is just the communication interface for connecting devices to a central system. Although it is not included in this example, in order to complete an IoT system, there is a need to perform data analysis, either in flight by using an event processing engine, or at rest by using solutions for machine learning. With a high degree of certainty, you will also need components that take advantage of key parts of this underlying technology to surface management and control mechanisms to users through the use of one or more portals, expose the gathered knowledge from machine learning to other parties through web services, and so on. d.Cost estimate calculationIn the previous sections of this paper, we discussed the various components that make up the cost for the data ingestion and communication platform inside the reference architecture. When we combine these, we can calculate the total estimated cost for a partition, and extrapolate the total estimated OPEX cost for the system based on the number of needed partitions using the following formula: 
Important topics not yet coveredIn this paper, we have strived to capture many of our learnings from implementing predictive maintenance solutions in the Internet of Things (IoT) space. However, in addition to the topics discussed, there is both much detail to add and more things to think about when architecting for IoT. This final section touches on some of these topics. e.Networks with automatic handover and fallbacksWhen we think about IoT scenarios, there seems to be an emerging need for networks working together in a seamless manner in order to provide frequently roaming users with the ability to perform command and control to either partially or fully closed IoT systems that they can access. This capability would require working across vendors and standards to ensure that the right connectivity type is available at the right time, and at the right price. f.The need for the commoditization of devicesMany solutions today use their own proprietary hub for connecting their point solution to the Internet. This approach needs to change, with vendors selling connectivity bridges that work much like today's home Internet routers. In fact, such Internet routers could prove to be a great point of integration with standardized PAN/LAN devices, and support autonomous operations when connectivity is not available. Ideally, these bridges would support current legacy non-IP PAN device protocols, such as Z-Wave, traditional ZigBee, and so on. g.The creation and use of information marketplacesAs IoT systems evolve, especially those capturing telemetry for intelligent decision making, there is a clear need for data augmentation to provide context for machine learning. Information marketplaces, such as Microsoft Azure DataMarket, need to expand their offerings, providing new opportunities for data providers. h.Management solutionsThere are standards put forth for managing devices95, such as OMA Device Management96 (of which Microsoft implemented a subset, called Mobile Device Management97), CPE WAN Management Protocol98, Lighweight M2M99, and UPnP-DM100. As millions of devices become part of IoT systems, there is a clear need for IoT solutions that can monitor and manage incidents in the systems, visualize information and effectively control the environment, and span the various connectivity options and supporting legacy systems. i.The redefinition of SLAsAlthough it represents a very hard problem to find a solution for, customers will ask for different types of Service Level Agreements (SLAs) in this space. Where current SLAs provide a system availability guarantee, this definition has to evolve to provide a concrete answer to questions, such as how much bandwidth is available, what is the maximum and average latency to expect, how many I/O operations per second (IOPS101) can the storage system provide, and do on. Moving beyond those basic guarantees, customers will seek answers from SaaS solutions for IoT based on simply the number of devices that they can support. j.Integration simplicityAs IoT promises to extend vertical solutions across horizontal markets, and connect systems in ways never seen before to add value to businesses and people’s lives, the integration between these systems and how they are secured needs to happen in a way that standardizes the integration. AMQP provides an example of this in regard to transport-layer integration. ConclusionsThis paper has gone into great detail about the particulars of building IoT solutions, based on our experience in working with enterprise customers. As you can see, IoT solutions can be complex but also offer massive promise for increasing revenue, cutting cost and finding new business models based on innovate use of technology. An enterprise might believe that its requirements are so unique that only a custom IoT solution can meet their needs. But the unusual requirements of IoT solutions in security, communication, and scale make them complex and expensive to build as custom solutions from the ground up. The Microsoft Azure platform, on the other hand, has a comprehensive set of building blocks that you need to build an IoT solution relatively quickly and painlessly by using the mentioned reference architecture. How Microsoft can help you succeedMicrosoft Services can help establish an effective strategy for your Predictive Maintenance scenario and provide direction, implementation guidance, delivery, and support to help your realize your Internet of Things strategy. We offer:
For more information about Consulting and Support solutions from Microsoft, contact your Microsoft Services representative or visit www.microsoft.com/services. 1 Microsoft, “What Our Customers Are Saying: Top Enterprise Trends of 2014,” Susan Houser 2 Wikipedia, Internet of Things 3 Gartner, IT Glossary, Internet of Things 4 Microsoft, “How Microsoft tech is helping affordable housing tenants save money” (section on “Captain”) 5 Deutsche Akademie der Technikwissenschaften, Final report of the Industrie 4.0 Working Group 6 General Electric, “Industrial Internet: Pushing the Boundaries of Minds and Machines, a European Perspective” 7 Gartner, “Gartner says the Internet of Things Installed Base Will Grow to 26 billion units by 2020”, December 2013 8 Microsoft, 10 reasons businesses need a strategy for the Internet of Things now 9 “From Machine-to-Machine to the Internet of Things: Introduction to a New Age of Intelligence”, ISBN 978-0124076846 10 United Nations, Economic & Social Affairs, World Population to 2300 11 Wikipedia, Service economy 12 For example, a network chip for less than $10 for 1,000 units. Texas Instruments, SimpleLink™ Wi-Fi Module CC3000 13 maxEmbedded, What is a microcontroller? And how does it differ from a microprocessor? 14 Texas Instruments, MSP430 documentation 15 Texas Instruments, Using power solutions to extend battery life in MSP430 applications 16 For a comprehensive list, see http://en.wikipedia.org/wiki/List_of_real-time_operating_systems 17 ITU-T, Internet of Things Global Standards Initiative 18 European Union, Internet of Things Architecture 19 “Samsung Simband aims to take a big step in wearable health,” www.cnet.com/products/samsung-simband/ 20 Microsoft Healthvault Medical Intelligent System, www.youtube.com/watch?v=j8Y4ukdNM60 21 Medical Design Technology Magazine, The Internet of Things and Medical Device Product Development: Practical Strategy Suggestions, March, 2014 22 YouTube, Medical Intelligent System, Proof of Concept 23 Deloitte, Networked medical device cybersecurity and patient safety: Perspectives of health care information cybersecurity executives 24 Texas Medical Association, Coding for Telephone Consultations 25 Wikipedia, OSI Model 26 Wikipedia, Duty Cycle 27 Georgia State University, ActSee: Activity-Aware Radio Duty Cycling for Sensor Networks in Smart Environments 28 Wikipedia, Cellular network 29 Ericsson Labs, “4G for IoT” 30 Wikipedia, IEEE 802.11, Protocols 31 IEEE, Transmission of IPv6 Packets over BLUETOOTH Low Energy 32 Wikipedia, Bluetooth Low Energy 33 Bluetooth SIG, A look at the Basics of Bluetooth Technology 35 ZigBee Alliance, ZigBee Specification Overview 36 ZigBee Alliance, ZigBee IP Specification Overview 37 Artem Dementyev, Steve Hodges, Stuart Taylor and Joshua Smith, Power Consumption Analysis of Bluetooth Low Energy, ZigBee and ANT Sensor Nodes in a Cyclic Sleep Scenario 38 Wireshark, Packet loss 39 Wikipedia, Transmission Control Protocol, Flow control 40 “Embedded”, Reworking the TCP/IP stack for use on embedded IoT devices 41 Association for Computing Machinery, Toward a Commodity Enterprise Middleware 42 See http://www.openamq.org 43 Apache, Apache Qpid™ 44 Microsoft, AMQP 1.0 support in Service Bus 45 See http://www.rabbitmq.com/ 46 Amqp.org, Products and success stories, Notable AMQP Users 48 Slideshare, Big Data at Aadhaar (slide 9) 49 OOI, CIAD COI TV RabbitMQ 50 Wikipedia, Constrained Application Protocol 51 Wikipedia, Wireless sensor network 52 Wikipedia, Wireless sensor network, Forest fire detection 53 Wikipedia, Structural health monitoring, Examples 54 See MQTT.org 55 OASIS, MQTT 3.1.1 draft 01 / public review draft 01 56 Wikipedia, Information Security, Authenticity 57 Wikipedia, Virtual private network 58 European Commission, Protection of Personal Data 59 US HHS, Health Information Privacy 60 US HHS, Privacy Act 61 TechRepublic, Data security laws and penalties: Pay IT now or pay out later 63 U.S. Department of Health & Human Services, Health Information Privacy, Business Associates 64 Microsoft, Azure HIPAA Implementation Guidance 65 Wikipedia, Network Address Translation 66 Wikipedia, Denial-of-service Attack 67 MSDN, Failsafe: Guidance for Resilient Cloud Architectures 68 MSDN, Cloud Development 69 MSDN, Service Bus 70 MSDN, Access Control Services 2.0 71 MSDN, Service Bus Queues, Topics, and Subscriptions 72 Microsoft, Service Bus Scalability 73 MSDN, Data Management Patterns and Guidance 74 See The 3 Vs of BIG data 75 Forbes, The Data Lake Dream 76 Teradata, Hot and Cold Running Data 77 MSDN, Circuit Breaker Pattern 79 Microsoft, StreamInsight 80 Apache, Storm, distributed and fault-tolerant realtime computation 81 Wikipedia, MapReduce 82 Wikipedia, MATLAB 83 Wikipedia, Apache Mahout 84 Wikipedia, R (programming language) 85 Techcrunch, Microsoft announces Azure ML, Cloud-based Machine Learning Platform That Can Predict Future Events 86 See https://datamarket.azure.com/ 87 Microsoft, Making Public Data Public 88 Odata, OData Home page 89 Microsoft, Microsoft Azure Marketplace Publishing 90 Microsoft, Microsoft Azure API Management 91 See http://azure.microsoft.com/en-us/pricing/details/event-hubs/. 92 Microsoft, Microsoft Azure, Event Hubs pricing, FAQ “What are throughput units and how are they billed?” 93 Microsoft, Microsoft Azure, Data Transfer Pricing Details 94 Microsoft, Microsoft Azure, Data Transfer Pricing Details 95 Blackberry, A Comparison of Protocols for Device Management and Software Updates 96 Wikipedia, OMA Device Management 97 Microsoft, MS-MDM: Mobile Device Management Protocol 98 Wikipedia, TR-069 99 Ericsson, “Lightweight M2M”: Enabling Device Management and Applications for the Internet of Things 100 See Introduction to UPnP Device Management 101 Wikipedia, IOPS Directory: download download -> Performance Tuning Guidelines for Windows Server 2008 May 20, 2009 Abstract download -> Northern England’s set-jetting locations download -> Bbc archives: Beyond the programme download download -> Occupational health and safety download -> Dynatest 3031 lwd light Weight Deflectometer download -> Forth coming competitive exams download -> English Olympiad Tasks: 10 th form 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