IOT_Workshop


About IOT Workshop

Internet of Things is a new revolution of the Internet. A world where the real, digital and the virtual are converging to create smart environments that make energy, transport, cities and many other areas more intelligent. A device become a smart device is called IOT. Now a days there are many android and server based application. In this system, value of sensor (e.g. temperature sensor, motion sensor, accelerometer sensor etc.) will be shown on GUI or web server or android application through wireless communication and device will be controlled automatically.Device will be operated on Wifi/GPRS.


General Issues

  1. The real value lies in the creation of new value propositions and potential revenue streams. The key is taking this technology and using it to move toward new business models and services that will help realize them. According to leading analysts and thought leaders, the growth potential is significant. The IoT market will hit $7.1 trillion in revenue by 2020. Gartner foresees the IoT install base growing to 26 billion units by 2020. And Cisco predicts that the IoT is poised to become a $19 trillion market.
  2. Historically, SCADA data has been locked away in somebody’s process control network. To access this information, update it, and revalidate it, people needed a miracle. With IoT, you can freely and quickly bring up this information when and where you need it. This one aspect is revolutionizing business models, allowing businesses to enhance their services in real time.
  3. Highly powerful tools developed for clickstream analysis, fraud detection, cyber security, and genome sequencing are now coming to process industries. Don’t snub other industries, thinking that you are different from them. They may have a few tricks in their pocket that you need.
  4. The more comparable assets are in your organization, the better your forecasts will be. Machine learning is better with more, similar data. Anything less leads to misconstrued information and inefficient.
  5. Data engineering can take significant time and resources. However, it shouldn’t stop you from moving forward with IoT initiatives. Instrumentation and controls engineers from the world of operational technology (OT) have to bridge the gap between the analytics and IT communities.
  6. In other words, cheap sensors are not going to be 100% reliable, 100% of the time. Physical damage during normal maintenance and operation in hostile industrial environments (such as dust, vibration, water, and caustic materials) will occur. Even sensor batteries can discharge. Ultimately, all sensors fail either instantaneously or slowly degrade. Processes must be established to make sure sensors are fully operational and deliver correct data.
  7. Reliability of predictions is only as good as the data feeding them. If you are going to run analytics based on sensor data, you better make sure that the sensor is in good working order. At times, you even have to go as far as validate the sensor data before it is reported or analyzed to answer critical business questions.
  8. To develop a model that forecasts behavior, data scientists require context and time-series data. Otherwise it becomes very difficult to consume this information and truly see what happening now and in the future. People need real-time data to make the best possible decisions. With pervasive monitoring, this information is captured and delivered for business intelligence analysis.
  9. IoT rollouts bring a proliferation of cheap, distributed sensors – resulting in a huge volume of data in a short amount of time. Is your infrastructure ready to support it?
  10. Data integration and actionable information are the heart of collection and analysis of IoT data. Invest in the technologies, expertise, and processes that support integration, reporting, decision making, and action – and maintain them well.