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Internet of Things Anatomy

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IoT platform as a regular server software. Types of platforms and its' communicaion with devices. Data normalization, storage, processing and visualization. IoT Platform Enterprise Integration. AggreGate Platform.

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Internet of Things Anatomy

  1. 1. Internet of Things Anatomy
  2. 2. Marketing experts introduced the Internet of Things • There was no revolution, just evolution • ‘Things’ have been communicating for quite a while (e.g. PLCs on a wire drawing line or network switches) • Monitoring and management systems have been existing for long, but again marketing experts sent them to the ‘cloud’ • Cellular and satellite modems weren’t invented yesterday • In fact IoT is just a general name joining various markets, both B2B and B2C • Terminology evolution: Intelligent Device Management => M2M => IoT - 2 -
  3. 3. Internet of Things comprises Devices (“things”) Data centers M2M concept assumes that devices interact with one another. They can do it: 1) Directly via network 2) Via network and central software in a data center (in the ‘cloud’) 3) Sometimes both Networks - 3 -
  4. 4. Device Network Structure IP TCP, UDP SNMP, Telnet, BACnet, Modbus, SOAP, HTTP, MQTT… RS-232, RS-485, Ethernet, Wi-Fi, USB, CAN, Bluetooth Z-Wave, GPRS/3G/LTE… PPP, ATM, SLIP… NetBIOS, PPTP, RPC… SSL, TLS... - 4 - OSI Network Model
  5. 5. Device Types The difference is in management software tasks. Example: GPS trackers for a dog and a bus are similar in terms of hardware, but they have absolutely different could services and dashboards. Consumer Industrial - 5 -
  6. 6. Device Logical Structure Variables (settings, properties): ability to read and write Such device structure is described in full or partially by any known communication protocol. Functions (methods, operations): ability to call and transmit input data while receiving output data Events (notifications): ability to subscribe and retrieve instances asynchronously Metadata (descriptions of available variables, functions and events) - 6 -
  7. 7. Internet of Things Platform • IoT platform is just a regular server software • It plays a role of runtime environment (application server) for IoT applications designed for the end user - 7 - • Only a few applications are written from scratch (will cover the reasons later) • IoT platforms are often deployed in rented commercial data centers, or in data centers belonging to large IoT device operators
  8. 8. Primary Objectives of IoT Platforms • Data collection from various devices and data sources • Storage of externally collected as well as internally generated data • Stand-alone data processing and automatic decision taking - 8 - • Data visualization (developing an operator interface) • Enterprise data integration (only for Industrial IoT) • Intelligent data exchange between devices
  9. 9. Types of IoT Platforms • Infrastructure platforms provide data storage and collection as well as API/SDK for implementing processing, visualization and integration methods (IoT application development) via programming • Full cycle platforms solve all tasks using visual constructors, with the only necessity for programming when writing communication modules and complex mathematics/logic - 9 -
  10. 10. Communication with Devices • Any IT (SNMP, Telnet, WMI...), automation (Modbus, BACnet, OPC…), IoT (MQTT, XMPP, AMQP…) and universal (HTTP/REST, SOAP, FTP…) protocols are used • Very few basic operations: reading and writing settings, executing operations, receiving events (including notifications on change in values) - 10 -
  11. 11. Data Normalization - 11 - Normalization is conversion to a unified standard form. It’s usually performed in two steps: • Abstraction from protocol (conversion to universal data types) • Abstraction from device type/make/version (application of device models)
  12. 12. Data Storage - 12 - What we store: • Server-side configuration and tools • Last device configuration snapshots (in case of unavailability) • Setting change history (for devices and server-side tools) • Event history (the same as above) Where we store: • Relational database (slow and inefficient) • NoSQL database (оптимально) • Specialized databases (e.g. RRD for time series aggregation – has its own pros and cons) RDBMS RRD (Statistics) NoSQL (Big Data)
  13. 13. Data Processing - 13 - • Completely standalone • Delayed group configuration and operation execution • Operator notifications upon important events and states (emails, SMS) • Dynamic models with own life cycle • Machine-readable knowledge base for taking decisions • Multiple tools (root cause analysis, scheduler, domain- specific languages – examples: AggreGate and IEC languages)
  14. 14. Data Visualization - 14 - • 1st and 2nd line operator interface is built from scratch for each IoT application • Interface base is a set of dashboards with navigation and drilldown • Dashboards include tables, forms, maps, facility plans, charts, diagrams and many other components • Everything is customizable till the very last pixel • Dynamic thanks to binding UI components to properties and events of a server data model
  15. 15. IoT Platform Enterprise Integration - 15 - • Uses the same protocols as for data collection • The protocols work the other way round • IoT doesn’t have typical integration scenarios • Configuration should be flexible but without programming
  16. 16. Why not to write everything yourself? - 16 - • A prototype will be ready quickly • You will spend years implementing a scalable system supporting failover clustering, distributed collection and storage architecture, etc. • A bicycle will be invented in about 5 years • There’ll be fixed expenses to support the real product state • It looks even more unnatural for system integrators, engineering companies and MSPs
  17. 17. Tibbo Systems and AggreGate Platform - 17 - • Tibbo Systems: Russian software developer working worldwide • AggreGate Platform: software “brick set” for building IoT device monitoring and management systems • 14-years’ investments into “brick” development • Hundreds of large installations in various countries • 10+ vertical market solutions, including IT infrastructure management and SCADA systems
  18. 18. Cases and References - 18 - • Monitoring and managing telecom tower power supply (Flexenclosure, Sweden) • Monitoring mission-critical uninterruptible power supply units (Unified Energy Corporation, Russia) • Narrow-band radio station monitoring system (DCI Tech, Canada) • Comprehensive monitoring of a multi-server telecom operator network (An-net, Russia) • Monitoring of engineer constructions (Insight, Russia) • Centralized fountain management (Sharel, Israel) • Roadheading equipment monitoring (Ilma, Russia)
  19. 19. Cases and References - 19 - • Building automation of the Electoral Commission of Namibia • Data acquisition from industrial alcohol breath testing devices (Intoximeters, the US) • Forklift fleet management and monitoring (Keytroller, the US) • Monitoring McAuto queue length and POS equipment (McDonald’s, the US) • Centralized monitoring, control and provisioning of Android-based vending machines (Minibar Systems, the US) • Cloud-based Time and Attendance system (RCPOnline, Poland) • Monitoring of a distributed IP-based emergency notification speakers network (Emergencies Ministry of Russia)

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