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Io t first(1)

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MuhammadAbduArRahman

The document discusses the key components of implementing an Internet of Things (IoT) system, including sensors, networks, standards, and intelligent data analysis. Sensors are used to collect device and environmental data, while networks transmit the sensor data. Standards are needed for aggregating and managing the large amounts of data. Intelligent data analysis then extracts insights from the data through techniques like artificial intelligence. Challenges include power consumption, security, interoperability, data volume and variety, and regulatory standards.

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LUPA GA SEMPAT GA TELITI TERBURU BURU Heinrich dalam bukunya berjudul "The Origin of Accident", menempatkan unsafe act sebagai penyumbang terbesar kecelakaan kerja, yakni sebanyak 88%. Anggapan unsafe act atau perilaku tidak aman sama halnya menganggap manusia sebagai akar masalah.
Internet of Things Evolusi Internet
a proposed development of the Internet in which everyday objects have network connectivity, allowing them to send and receive data.
Io t first(1)
Why Internet of Things is Needed? • IoT akan mengubah dan menyelamatkan hidup • IoT akan mengubah industri yang ada dan membuatnya menjadi baru. • IoT akan menjadi hal yang biasa.
Benefits Internet of Things? • Safety, Comfort, Efficiency • Better Decision Making • Revenue Generation
Threats Internet of Things? • Security and Privacy • Data and Complexity • Business and IT Buy-in
Perangkat IoT (Embedded device) • Sensor/Input • CPU/komputer/single board computer/microcontroller MCU(Arduino Uno R3, Raspberry Pi, Intel Galileo dll) • Sistem Operasi (Google Brillo, Windows 10 IOT OS, ARM mbed OS, Huawei LiteOS, Intel RealSense OS X) • Jalur komunikasi (bluetooth, wifi, internet) • Output
Embedded Operating System • RIOT OS • Windows 10 For IoT • WindRiver VxWorks • Google Brillo • ARM Mbed OS • Embedded Apple iOS And OS X • Nucleus RTOS • Green Hills Integrity
How the Internet of Things Works?
What is an IoT Platform? The IoT platform is a suite of components that enable: Deployment of applications that monitor, manage, and control connected devices. Remote data collection from connected devices. Independent and secure connectivity between devices. Device/sensor management.
Io t first(1)
The 8 components of an IoT Application Enablement Platform (Source: IoT Analytics) Connectivity & normalization: brings different protocols and different data formats into one “software” interface ensuring accurate data streaming and interaction with all devices. Device management: ensures the connected “things” are working properly, seamlessly running patches and updates for software and applications running on the device or edge gateways. Database: scalable storage of device data brings the requirements for hybrid cloud-based databases to a new level in terms of data volume, variety, velocity and veracity. Processing & action management: brings data to life with rule-based event- action-triggers enabling execution of “smart” actions based on specific sensor data.
Analytics: performs a range of complex analysis from basic data clustering and deep machine learning to predictive analytics extracting the most value out of the IoT data-stream. Visualization: enables humans to see patterns and observe trends from visualization dashboards where data is vividly portrayed through line-, stacked-, or pie charts, 2D- or even 3D-models. Additional tools: allow IoT developers prototype, test and market the IoT use case creating platform ecosystem apps for visualizing, managing and controlling connected devices. External interfaces: integrate with 3rd-party systems and the rest of the wider IT-ecosystem via built-in application programming interfaces (API), software development kits (SDK), and gateways.
Io t first(1)
Different entry strategies into the IoT Platform market • Organic bottom-up approach: Starting with the connectivity part and building out platform features from the bottom-up (e.g., Ayla Networks) • Organic top-down approach: Starting with the analytics part and building out platform features from the top-down (e.g., IBM IoT Foundation) • Partnership approach: Striking alliances to offer the full package (e.g., GE Predix & PTC Thingworx) • M&A approach: Targeted acquisitions (e.g., Amazon – 2lemetry) or contenders performing strategic mergers (e.g., Nokia & Alcatel-Lucent) • Investment approach: Tactical investments throughout the IoT ecosystem (e.g., Cisco).
IoT Software Platform Device management? Integration Security Protocols for data collection Types of analytics Support for visualizations? 2lemetry - IoT Analytics Platform** Yes Salesforce, Heroku, ThingWorx APIs Link Encryption (SSL), Standards ( ISO 27001, SAS70 Type II audit) MQTT, CoAP, STOMP,M3DA Real-time analytics (Apache Storm) No Appcelerator No REST API Link Encryption (SSL, IPsec, AES-256) MQTT, HTTP Real-time analytics (Titanium [1]) Yes (Titanium UI Dashboard) AWS IoT platform Yes REST API Link Encryption (TLS), Authentication (SigV4, X.509) MQTT, HTTP1.1 Real-time analytics (Rules Engine, Amazon Kinesis, AWS Lambda) Yes (AWS IoT Dashboard) Bosch IoT Suite - MDM IoT Platform Yes REST API *Unknown MQTT, CoAP, AMQP,STOMP *Unknown Yes (User Interface Integrator) Ericsson Device Connection Platform (DCP) - MDM IoT Platform Yes REST API Link Encryption (SSL/TSL),Authentication (SIM based) CoAP *Unknown No EVRYTHNG - IoT Smart Products Platform No REST API Link Encryption (SSL) MQTT,CoAP, WebSockets Real-time analytics (Rules Engine) Yes (EVRYTHNG IoT Dashboard) IBM IoT Foundation Device Cloud Yes REST and Real-time APIs Link Encryption ( TLS), Authentication (IBM Cloud SSO), Identity management (LDAP) MQTT, HTTPS Real-time analytics (IBM IoT Real-Time Insights) Yes (Web portal) ParStream - IoT Analytics Platform*** No R, UDX API *Unknown MQTT Real-time analytics, Batch analytics (ParStream DB) Yes (ParStream Management Console) PLAT.ONE - end-to-end IoT and M2M application platform Yes REST API Link Encryption (SSL), Identity Management (LDAP) MQTT, SNMP *Unknown Yes (Management Console for application enablement, data management, and device management) ThingWorx - MDM IoT Platform Yes REST API Standards (ISO 27001), Identity Management (LDAP) MQTT, AMQP, XMPP, CoAP, DDS, WebSockets Predictive analytics(ThingWorx Machine Learning), Real- time analytics (ParStream DB) Yes (ThingWorx SQUEAL) Xively- PaaS enterprise IoT platform No REST API Link Encryption (SSL/TSL) HTTP, HTTPS, Sockets/ Websocket, MQTT *Unknown Yes (Management console)
IoT standardization components
IoT standardization components • Platform: This part includes the form and design of the products (UI/UX), analytics tools used to deal with the massive volume of data streaming from all products in a secure way, and scalability which means that wide adoption of protocols like IPv6 in all vertical and horizontal markets is needed. • Connectivity: This phase includes all parts of the consumer's day and night routine, from using wearables, smart cars, smart homes, and in the big scheme, smart cities. From the business prospective we have connectivity using IIoT (Industrial Internet of Things) where M2M communications dominate the field.
IoT standardization components • Business Model: The bottom line is a big motivation for starting, investing in, and operating any business; without a sound and solid business model for IoT we will have another bubble , this model must satisfied all the requirements for all kinds of e-commerce; vertical markets, horizontal markets and consumer markets. But this category is always a victim of regulatory and legal scrutiny. • Killer Applications: In this category there are three functions needed to have killer applications: control "things", collect "data", and analyze "data". IoT needs killer applications to drive the business model using a unified platform.
IoT implementation components
IoT implementation components • Sensors There two types of sensor: active sensors and passive sensors. The driving forces for using sensors in IoT today are new trends in technology that have made sensors cheaper, smarter and smaller. The challenges facing IoT sensors are: power consumption, security, and interoperability.
• Networks The second component of IoT implementation is to transmit the signals collected by sensors over networks with all the different components of a typical network including routers, bridges in different topologies. Connecting the different parts of networks to the sensors can be done by different technologies including Wi-Fi, Bluetooth, Low Power Wi-Fi, WiMAX, regular Ethernet, Long Term Evolution (LTE) and the recent promising technology of Li-Fi (using light as a medium of communication between the different parts of a typical network including sensors). The driving forces for widespread network adoption in IoT are high data rate, low prices of data usage, virtualization (X - Defined Network trends), XaaS concept (SaaS, PaaS, and IaaS), and IPv6 deployment. But the challenges facing network implementation in IoT are the enormous growth in the number of connected devices, availability of network coverage, security, and power consumption.
• Standards The third stage in the implementation process involves the sum of all activities of handling, processing and storing the data collected from the sensors. This aggregation increases the value of data by increasing the scale, scope, and frequency of data available for analysis. But aggregation can only be achieved through the use of various standards depending on the IoT application in use. There are two types of standards relevant for the aggregation process; technology standards (including network protocols, communication protocols, and data-aggregation standards) and regulatory standards (related to security and privacy of data, among other issues). Challenges facing the adoption of standards within IoT are: standards for handling unstructured data, security and privacy issues in addition to regulatory standards for data markets.
• Intelligent analysis The fourth stage in IoT implementation is extracting insight from data for analysis. IoT analysis is driven by cognitive technologies and the accompanying models that facilitate the use of cognitive technologies. With advances in cognitive technologies' ability to process varied forms of information, vision and voice have also become usable, and open the doors for in-depth understanding of the non-stop streams of real-time data. Factors driving adoption of intelligent analytics within the IoT include artificial intelligence models, growth in crowdsourcing and open- source analytics software, real-time data processing and analysis. Challenges facing the adoption of analytics within IoT; inaccurate analysis due to flaws in the data and/or model, legacy systems' ability to analyze unstructured data, and legacy systems' ability to manage real-time data.
• Intelligent actions Intelligent actions can be expressed as M2M (Machine to Machine) and M2H (Machine to Human) interfaces for example with all the advancement in UI and UX technologies. Factors driving adoption of intelligent actions within the IoT; lower machine prices, improved machine functionality, machines "influencing" human actions through behavioral-science rationale, and deep learning tools. Challenges facing the adoption of intelligent actions within IoT: machines' actions in unpredictable situations, information security and privacy, machine interoperability, mean-reverting human behaviors, and slow adoption of new technologies
Protokol Protokol adalah sebuah aturan atau standar yang mengatur atau mengijinkan terjadinya hubungan, komunikasi, dan perpindahan data antara dua atau lebih titik komputer. Protokol dapat diterapkan pada perangkat keras, perangkat lunak atau kombinasi dari keduanya. Pada tingkatan yang terendah, protokol mendefinisikan koneksi perangkat keras.
Fungsi Protokol a. Fragmentasi dan Re-assembly Pembagian informasi yang dikirim menjadi beberapa paket data dari sisi pengirim. Jika telah sampai di penerima, paket data tersebut akan digabungkan menjadi paket berita yang lengkap. b. Enkapsulasi Enkapsulasi (Encaptulation) adalah proses pengiriman data yang dilengkapi dengan alamat, kode-kode koreksi, dan lain-lain. c. Kontrol Konektivitas Membangun hubungan komunikasi berupa pengiriman data dan mengakhiri hubungan dari pengirim ke penerima. d. Flow Control Fungsi dari Flow Control adalah sebagai pengatur jalannya data dari pengirim ke penerima. e. Error Control Tugasnya adalah mengontrol terjadinya kesalahan sewaktu data dikirimkan. f. Pelayanan Transmisi Fungsinya adalah memberikan pelayanan komunikasi data yang berhubungan dengan prioritas dan keamanan data.
M2M M2M adalah terminologi dari "Machine-to-Machine", merupakan salah satu dari bidang kategori ICT (Information and Communication Technology), yaitu penggabungan teknologi komunikasi, komputer dan daya sehingga memungkinkan terjadinya komunikasi jarak jauh antara manusia dan mesin melalui interaksi fisik, kimia serta sistem dan proses biologi. Sebagai tambahan, M2M merupakan aplikasi komputasi baru dimana data dialirkan dari dan ke fisik serta biologi.
OneM2M oneM2M adalah sebuah standar global terkemuka untuk m2m(komunikasi machine to machine) dan juga IoT. Dibentuk melalui gabungan beberapa standar organisasi untuk mengembangkan suatu platform horizontal untuk pertukaran dan berbagi data antara beberapa aplikasi. oneM2M membuat distribusi software layer seperti sistem operasi, yang memfasilitasi penggabungan dengan menyediakan kerangka untuk interworking dengan teknologi yang berbeda. Inti dari 2 elemen terpenting dari oneM2M : menyediakan interworking framework dan memungkinkan menggunakan kembali apa yang sudah tersedia sebanyak mungkin yang bisa digunakan.

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Io t first(1)

  • 1. LUPA GA SEMPAT GA TELITI TERBURU BURU Heinrich dalam bukunya berjudul "The Origin of Accident", menempatkan unsafe act sebagai penyumbang terbesar kecelakaan kerja, yakni sebanyak 88%. Anggapan unsafe act atau perilaku tidak aman sama halnya menganggap manusia sebagai akar masalah.
  • 3. a proposed development of the Internet in which everyday objects have network connectivity, allowing them to send and receive data.
  • 5. Why Internet of Things is Needed? • IoT akan mengubah dan menyelamatkan hidup • IoT akan mengubah industri yang ada dan membuatnya menjadi baru. • IoT akan menjadi hal yang biasa.
  • 6. Benefits Internet of Things? • Safety, Comfort, Efficiency • Better Decision Making • Revenue Generation
  • 7. Threats Internet of Things? • Security and Privacy • Data and Complexity • Business and IT Buy-in
  • 8. Perangkat IoT (Embedded device) • Sensor/Input • CPU/komputer/single board computer/microcontroller MCU(Arduino Uno R3, Raspberry Pi, Intel Galileo dll) • Sistem Operasi (Google Brillo, Windows 10 IOT OS, ARM mbed OS, Huawei LiteOS, Intel RealSense OS X) • Jalur komunikasi (bluetooth, wifi, internet) • Output
  • 9. Embedded Operating System • RIOT OS • Windows 10 For IoT • WindRiver VxWorks • Google Brillo • ARM Mbed OS • Embedded Apple iOS And OS X • Nucleus RTOS • Green Hills Integrity
  • 10. How the Internet of Things Works?
  • 11. What is an IoT Platform? The IoT platform is a suite of components that enable: Deployment of applications that monitor, manage, and control connected devices. Remote data collection from connected devices. Independent and secure connectivity between devices. Device/sensor management.
  • 13. The 8 components of an IoT Application Enablement Platform (Source: IoT Analytics) Connectivity & normalization: brings different protocols and different data formats into one “software” interface ensuring accurate data streaming and interaction with all devices. Device management: ensures the connected “things” are working properly, seamlessly running patches and updates for software and applications running on the device or edge gateways. Database: scalable storage of device data brings the requirements for hybrid cloud-based databases to a new level in terms of data volume, variety, velocity and veracity. Processing & action management: brings data to life with rule-based event- action-triggers enabling execution of “smart” actions based on specific sensor data.
  • 14. Analytics: performs a range of complex analysis from basic data clustering and deep machine learning to predictive analytics extracting the most value out of the IoT data-stream. Visualization: enables humans to see patterns and observe trends from visualization dashboards where data is vividly portrayed through line-, stacked-, or pie charts, 2D- or even 3D-models. Additional tools: allow IoT developers prototype, test and market the IoT use case creating platform ecosystem apps for visualizing, managing and controlling connected devices. External interfaces: integrate with 3rd-party systems and the rest of the wider IT-ecosystem via built-in application programming interfaces (API), software development kits (SDK), and gateways.
  • 16. Different entry strategies into the IoT Platform market • Organic bottom-up approach: Starting with the connectivity part and building out platform features from the bottom-up (e.g., Ayla Networks) • Organic top-down approach: Starting with the analytics part and building out platform features from the top-down (e.g., IBM IoT Foundation) • Partnership approach: Striking alliances to offer the full package (e.g., GE Predix & PTC Thingworx) • M&A approach: Targeted acquisitions (e.g., Amazon – 2lemetry) or contenders performing strategic mergers (e.g., Nokia & Alcatel-Lucent) • Investment approach: Tactical investments throughout the IoT ecosystem (e.g., Cisco).
  • 17. IoT Software Platform Device management? Integration Security Protocols for data collection Types of analytics Support for visualizations? 2lemetry - IoT Analytics Platform** Yes Salesforce, Heroku, ThingWorx APIs Link Encryption (SSL), Standards ( ISO 27001, SAS70 Type II audit) MQTT, CoAP, STOMP,M3DA Real-time analytics (Apache Storm) No Appcelerator No REST API Link Encryption (SSL, IPsec, AES-256) MQTT, HTTP Real-time analytics (Titanium [1]) Yes (Titanium UI Dashboard) AWS IoT platform Yes REST API Link Encryption (TLS), Authentication (SigV4, X.509) MQTT, HTTP1.1 Real-time analytics (Rules Engine, Amazon Kinesis, AWS Lambda) Yes (AWS IoT Dashboard) Bosch IoT Suite - MDM IoT Platform Yes REST API *Unknown MQTT, CoAP, AMQP,STOMP *Unknown Yes (User Interface Integrator) Ericsson Device Connection Platform (DCP) - MDM IoT Platform Yes REST API Link Encryption (SSL/TSL),Authentication (SIM based) CoAP *Unknown No EVRYTHNG - IoT Smart Products Platform No REST API Link Encryption (SSL) MQTT,CoAP, WebSockets Real-time analytics (Rules Engine) Yes (EVRYTHNG IoT Dashboard) IBM IoT Foundation Device Cloud Yes REST and Real-time APIs Link Encryption ( TLS), Authentication (IBM Cloud SSO), Identity management (LDAP) MQTT, HTTPS Real-time analytics (IBM IoT Real-Time Insights) Yes (Web portal) ParStream - IoT Analytics Platform*** No R, UDX API *Unknown MQTT Real-time analytics, Batch analytics (ParStream DB) Yes (ParStream Management Console) PLAT.ONE - end-to-end IoT and M2M application platform Yes REST API Link Encryption (SSL), Identity Management (LDAP) MQTT, SNMP *Unknown Yes (Management Console for application enablement, data management, and device management) ThingWorx - MDM IoT Platform Yes REST API Standards (ISO 27001), Identity Management (LDAP) MQTT, AMQP, XMPP, CoAP, DDS, WebSockets Predictive analytics(ThingWorx Machine Learning), Real- time analytics (ParStream DB) Yes (ThingWorx SQUEAL) Xively- PaaS enterprise IoT platform No REST API Link Encryption (SSL/TSL) HTTP, HTTPS, Sockets/ Websocket, MQTT *Unknown Yes (Management console)
  • 19. IoT standardization components • Platform: This part includes the form and design of the products (UI/UX), analytics tools used to deal with the massive volume of data streaming from all products in a secure way, and scalability which means that wide adoption of protocols like IPv6 in all vertical and horizontal markets is needed. • Connectivity: This phase includes all parts of the consumer's day and night routine, from using wearables, smart cars, smart homes, and in the big scheme, smart cities. From the business prospective we have connectivity using IIoT (Industrial Internet of Things) where M2M communications dominate the field.
  • 20. IoT standardization components • Business Model: The bottom line is a big motivation for starting, investing in, and operating any business; without a sound and solid business model for IoT we will have another bubble , this model must satisfied all the requirements for all kinds of e-commerce; vertical markets, horizontal markets and consumer markets. But this category is always a victim of regulatory and legal scrutiny. • Killer Applications: In this category there are three functions needed to have killer applications: control "things", collect "data", and analyze "data". IoT needs killer applications to drive the business model using a unified platform.
  • 22. IoT implementation components • Sensors There two types of sensor: active sensors and passive sensors. The driving forces for using sensors in IoT today are new trends in technology that have made sensors cheaper, smarter and smaller. The challenges facing IoT sensors are: power consumption, security, and interoperability.
  • 23. • Networks The second component of IoT implementation is to transmit the signals collected by sensors over networks with all the different components of a typical network including routers, bridges in different topologies. Connecting the different parts of networks to the sensors can be done by different technologies including Wi-Fi, Bluetooth, Low Power Wi-Fi, WiMAX, regular Ethernet, Long Term Evolution (LTE) and the recent promising technology of Li-Fi (using light as a medium of communication between the different parts of a typical network including sensors). The driving forces for widespread network adoption in IoT are high data rate, low prices of data usage, virtualization (X - Defined Network trends), XaaS concept (SaaS, PaaS, and IaaS), and IPv6 deployment. But the challenges facing network implementation in IoT are the enormous growth in the number of connected devices, availability of network coverage, security, and power consumption.
  • 24. • Standards The third stage in the implementation process involves the sum of all activities of handling, processing and storing the data collected from the sensors. This aggregation increases the value of data by increasing the scale, scope, and frequency of data available for analysis. But aggregation can only be achieved through the use of various standards depending on the IoT application in use. There are two types of standards relevant for the aggregation process; technology standards (including network protocols, communication protocols, and data-aggregation standards) and regulatory standards (related to security and privacy of data, among other issues). Challenges facing the adoption of standards within IoT are: standards for handling unstructured data, security and privacy issues in addition to regulatory standards for data markets.
  • 25. • Intelligent analysis The fourth stage in IoT implementation is extracting insight from data for analysis. IoT analysis is driven by cognitive technologies and the accompanying models that facilitate the use of cognitive technologies. With advances in cognitive technologies' ability to process varied forms of information, vision and voice have also become usable, and open the doors for in-depth understanding of the non-stop streams of real-time data. Factors driving adoption of intelligent analytics within the IoT include artificial intelligence models, growth in crowdsourcing and open- source analytics software, real-time data processing and analysis. Challenges facing the adoption of analytics within IoT; inaccurate analysis due to flaws in the data and/or model, legacy systems' ability to analyze unstructured data, and legacy systems' ability to manage real-time data.
  • 26. • Intelligent actions Intelligent actions can be expressed as M2M (Machine to Machine) and M2H (Machine to Human) interfaces for example with all the advancement in UI and UX technologies. Factors driving adoption of intelligent actions within the IoT; lower machine prices, improved machine functionality, machines "influencing" human actions through behavioral-science rationale, and deep learning tools. Challenges facing the adoption of intelligent actions within IoT: machines' actions in unpredictable situations, information security and privacy, machine interoperability, mean-reverting human behaviors, and slow adoption of new technologies
  • 27. Protokol Protokol adalah sebuah aturan atau standar yang mengatur atau mengijinkan terjadinya hubungan, komunikasi, dan perpindahan data antara dua atau lebih titik komputer. Protokol dapat diterapkan pada perangkat keras, perangkat lunak atau kombinasi dari keduanya. Pada tingkatan yang terendah, protokol mendefinisikan koneksi perangkat keras.
  • 28. Fungsi Protokol a. Fragmentasi dan Re-assembly Pembagian informasi yang dikirim menjadi beberapa paket data dari sisi pengirim. Jika telah sampai di penerima, paket data tersebut akan digabungkan menjadi paket berita yang lengkap. b. Enkapsulasi Enkapsulasi (Encaptulation) adalah proses pengiriman data yang dilengkapi dengan alamat, kode-kode koreksi, dan lain-lain. c. Kontrol Konektivitas Membangun hubungan komunikasi berupa pengiriman data dan mengakhiri hubungan dari pengirim ke penerima. d. Flow Control Fungsi dari Flow Control adalah sebagai pengatur jalannya data dari pengirim ke penerima. e. Error Control Tugasnya adalah mengontrol terjadinya kesalahan sewaktu data dikirimkan. f. Pelayanan Transmisi Fungsinya adalah memberikan pelayanan komunikasi data yang berhubungan dengan prioritas dan keamanan data.
  • 29. M2M M2M adalah terminologi dari "Machine-to-Machine", merupakan salah satu dari bidang kategori ICT (Information and Communication Technology), yaitu penggabungan teknologi komunikasi, komputer dan daya sehingga memungkinkan terjadinya komunikasi jarak jauh antara manusia dan mesin melalui interaksi fisik, kimia serta sistem dan proses biologi. Sebagai tambahan, M2M merupakan aplikasi komputasi baru dimana data dialirkan dari dan ke fisik serta biologi.
  • 30. OneM2M oneM2M adalah sebuah standar global terkemuka untuk m2m(komunikasi machine to machine) dan juga IoT. Dibentuk melalui gabungan beberapa standar organisasi untuk mengembangkan suatu platform horizontal untuk pertukaran dan berbagi data antara beberapa aplikasi. oneM2M membuat distribusi software layer seperti sistem operasi, yang memfasilitasi penggabungan dengan menyediakan kerangka untuk interworking dengan teknologi yang berbeda. Inti dari 2 elemen terpenting dari oneM2M : menyediakan interworking framework dan memungkinkan menggunakan kembali apa yang sudah tersedia sebanyak mungkin yang bisa digunakan.