Iot trends and technologies development in terms of Machine Learning

1 Jul 2020

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Iot trends and technologies development in terms of Machine Learning

  2. Mr.Janarthanan.S Assistant Professor, School of Computing Science and Engineering Galgotias University, Uttar Pradesh
  3.  About IoT  Trends & Technologies  IoT Applications Ranking  Machine Learning  Tools and courses for further learning  IoT development in Future  Conclusion 3
  4.  Formal Definition: The Internet of things (IoT) is a system of interrelated computing devices, mechanical and digital machines provided with unique identifiers (UIDs) and the ability to transfer data over a network without requiring human-to-human or human-to- computer interaction. 4
  5.  Simple words? "A network of Internet connected objects able to collect and exchange data.“ It is commonly abbreviated as IoT. ... In a simple way to put it, You have "things" that sense and collect data and send it to the internet.  Who invented IoT? Kevin Ashton is sometimes called the “Inventor of IoT” since the first used the term in 1999 to describe a system where the Internet is connected to the physical world via ubiquitous sensors. He is a serial entrepreneur and co-founded the Auto-ID Center at MIT 5
  6.  How it works? An IoT system consists of sensors/devices which “talk” to the cloud through some kind of connectivity. Once the data gets to the cloud, software processes it and then might decide to perform an action, such as sending an alert or automatically adjusting the sensors/devices without the need for the user. 6
  7.  What is IoT and its applications? IoT is essentially a platform where embedded devices are connected to the internet, so they can collect and exchange data with each other. It enables devices to interact, collaborate and, learn from each other's experiences just like humans do 7
  8.  Why is IoT important? Since IoT generates and analyzes vast amounts of data, it is a significant driver of big data analytics projects. In particular, it can deliver large amounts of data in real- time. ... Through various IoT devices, it is possible to monitor the performance of all employees as well as improve operations at all locations 8
  9.  What is IoT example? Objects that can fall into the scope of Internet of Things include connected security systems, thermostats, cars, electronic appliances, lights in household and commercial environments, alarm clocks, speaker systems, vending machines and more. 9
  10.  What is the best example of an IoT device? Consumer connected devices include smart TVs, smart speakers, toys, wearable's and smart appliances. Smart meters, commercial security systems and smart city technologies -- such as those used to monitor traffic and weather conditions -- are examples of industrial and enterprise IoT devices. 10
  11.  Where is IoT used? IoT devices can be used to monitor and control the mechanical, electrical and electronic systems used in various types of buildings (e.g., public and private, industrial, institutions, or residential) in home automation and building automation systems. 11
  12.  What is IoT and its benefits? The IoT allows you to automate and control the tasks that are done on a daily basis, avoiding human intervention. Machine- to-machine communication helps to maintain transparency in the processes. It also leads to uniformity in the tasks. It can also maintain the quality of service. 12
  13.  How IoT affect our life? Along with advanced data analytics, IoT- enabled devices and sensors are helping us reduce air pollution in some of our world's biggest cities, improve agriculture and our food supply, and even detect and contain deadly viruses. More than half of the world's population now lives in cities—up from just 34% in the 1960s. 13
  14.  What is IoT in our life? The Internet of Things (IoT) refers to devices such as cell phones, vehicles, electronic appliances, and smart sensors that are connected to a wireless network. ... IoT devices will have a significant impact on many aspects of our lives including how we live, drive, and farm animals and crops. 14
  15.  Is IoT the future? IOT means Internet Of Things. IOT comprises of sensors, smart meters, smart vehicles connected to Internet. ... By 2022, it's estimated that there will be 30 billion IoT devices, and a global market of $7.1 trillion. Without a doubt, IoT is poised to play a central and defining role in the future of the world. 15
  16.  6 Leading Types of IoT Wireless Tech and Their Best Use Cases 16Source:
  17.  6 Leading Types of IoT Wireless Tech and Their Best Use Cases  1. LPWANs  Low Power Wide Area Networks (LPWANs) are the new phenomenon in IoT. By providing long-range communication on small, inexpensive batteries  This family of technologies is purpose-built to support large-scale IoT networks sprawling over vast industrial and commercial  LPWANs can literally connect all types of IoT sensors – facilitating numerous applications from remote monitoring, smart metering and worker safety to building controls and facilitymanagement. 17Source:
  18.  2. Cellular (3G/4G/5G)  Well-established in the consumer mobile market, cellular networks offer reliable broadband communication supporting various voice calls and video streaming applications.  On the downside, they impose very high operational costs and power requirements.  The majority of IoT applications powered by battery-operated sensor networks, they fit well in specific use cases such as connected cars or fleet management in transportation and logistics.  Cellular next-gen 5G with high-speed mobility support and ultra-low latency is positioned to be the future of autonomous vehicles and augmented reality. 5G is also expected to enable real-time video surveillance for public safety, real-time mobile delivery of medical data sets for connected health, and several time-sensitive industrial automation applications in the future 18Source:
  19.  3. Zigbee and Other Mesh Protocols  Zigbee is a short-range, low-power, wireless standard (IEEE 802.15.4), commonly deployed in mesh topology to extend coverage by relaying sensor data over multiple sensor nodes.  Compared to LPWAN, Zigbee provides higher data rates, but at the same time, much less power-efficiency due to mesh configuration.  Because of their physical short-range (< 100m), Zigbee and similar mesh protocols (e.g. Z-Wave, Thread etc.) are best- suited for medium-range IoT applications with an even distribution of nodes in close proximity  Zigbee is a perfect complement to Wi-Fi for various home automation use cases like smart lighting, HVAC controls, security and energy management, etc. – leveraging home sensor networks. 19Source:
  20.  4. Bluetooth and BLE  Bluetooth is a short-range communication technology well-positioned in the consumer marketplace.  Bluetooth Classic was originally intended for point-to- point or point-to-multipoint (up to seven slave nodes) data exchange among consumer devices  Optimized for power consumption, Bluetooth Low- Energy was later introduced to address small- scale Consumer IoT applications.  BLE is widely integrated into fitness and medical wearables (e.g. smartwatches, glucose meters, pulse oximeters, etc.) as well as Smart Home devices (e.g. door locks) 20Source:
  21.  5. Wi-Fi  its major limitations in coverage, scalability and power consumption make the technology much less prevalent.  Wi-Fi is often not a feasible solution for large networks of battery-operated IoT sensors, especially in industrial IoT and smart building scenarios.  Instead, it more pertains to connecting devices that can be conveniently connected to a power outlet like smart home gadgets and appliances, digital signage's or security cameras.  Wi-Fi 6 – the newest Wi-Fi generation – brings in greatly enhanced network bandwidth (i.e. <9.6 Gbps) to improve data throughput per user in congested environments. 21Source:
  22.  6. RFID  Radio Frequency Identification (RFID) uses radio waves to transmit small amounts of data from an RFID tag to a reader within a very short distance  Till now, the technology has facilitated a major revolution in retail and logistics. 22Source:
  23. 23Source: Use-Cases-for-Different-IoT-Wireless-Tech
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  25. 25  What is machine learning in IoT?  Rapid developments in hardware, software, and communication technologies have facilitated the emergence of Internet-connected sensory devices that provide observations and data measurements from the physical world. ...  The potential and challenges of machine learning for IoT data analytics will also be discussed
  26. 26  Is machine learning related to IoT?  Machine learning has experienced a boost in popularity among industrial companies thanks to the hype surrounding the Internet of Things (IoT).  Simply the promise of a cloud-based IoT platform is not enough. Sensors connected to the IoT networks and the data generated from the sensors needs to be analysed
  27. 27  Which is better IoT or machine learning?  Machine learning and deep learning require massive amounts of data to work, and this data is being collected by the billions of sensors that are continuing to come online in the Internet of Things. IoT makes better AI.  What is IoT and ML training?  ML is becoming an essential player in a growing array of process areas involving image recognition, natural language processing, forecasting, prediction, and process optimization.
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  29. 29  IBM Watson Studio  Watson Studio lets you build and deploy an AI solution, using the best of open source and IBM software and giving your team a single environment to work in.  Hands on Labs ---->  IBM® Watson Studio - Speed up ML/DL development with Modeler Flows  Watson-Studio/
  30. 30  Automating IoT Machine Learning: Bridging Cloud and Device Benefits with AI Platform  -iot-machine-learning  Machine Learning with IoT Devices on the Edge  us/archive/msdn-magazine/2018/july/machine- learning-machine-learning-with-iot-devices-on- the-edge
  31. 31  Machine Learning for IoT  Ekkono connected things smart. Ekkono’s Edge Machine Learning software is embedded onboard connected devices to make them conscious, self- learning, and predictive.   GIT HUB Built for developers  GitHub is a development platform inspired by the way you work. From open source to business, you can host and review code, manage projects, and build software alongside 50 million developers. 
  32. 32  Amazon SageMaker  Machine learning for every developer and data scientist  sagemaker/?trk=ps_a134p000006BnGnAAK&trkCampaign=2020_HowMLisDone_campaign_landing_page&sc_channel= ps&sc_campaign=SM_AD_Google_CL_RSA_SMML_PNB&sc_outcome=AIML_Digital_Marketing&sc_geo=mult&sc_countr y=mult&sc_publisher=Google&s_kwcid=AL!4422!3!428016792162!b!!g!!ai%20and%20machine%20learning&sc_detail= ai%20and%20machine%20learning&ef_id=EAIaIQobChMIkLu22OWX6gIVgn8rCh2qdAcaEAAYBCAAEgLwc_D_BwE:G:s&s_ kwcid=AL!4422!3!428016792162!b!!
  33. 33  Introduction to internet of things By Prof. Sudip Misra | IIT Kharagpur  Introduction to Machine Learning By Prof. Balaraman Ravindran | IIT Madras  Practical Machine Learning with Tensorflow By Prof. Ashish Tendulkar, Prof. Balaraman Ravindran | Google, IIT Madras
  34. 34  10 Predictions about the future of IoT.  1.By 2025, it is estimated that there will be more than to 21 billion IoT devices  2. Cybercriminals will continue to use IoT devices to facilitate DDoS attacks  3. More cities will become “smart”  4. Artificial intelligence will continue to become a bigger thing Source:
  35. 35  5. Routers will continue to become more secure and smarter  6. 5G Networks will continue to fuel IoT growth  7. Cars will get even smarter  8. 5G’s arrival will also open the door to new privacy and security concerns  9. IoT-based DDoS attacks will take on more dangerous forms  10. Security and privacy concerns will drive legislation and regulatory activity Source:
  36.  Be Ready with IoT & Machine Learning for future growth and development  Train yourself with recent trends and technologies related to that always 36
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