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  1. Introduction: Data Analytics has traditionally been associated with the processes involved in using data to inform decision making. It builds on the underpinning principles of data management that are required to build any kind of IT system, including the integration of IoT operational and back-end business systems. In the context of IoT, Data analytics encompasses many approaches including big data, in-memory computing, cloud computing, NoSQL databases, data integration, and interactive analytics, as shown in the diagram below. Diagram courtesy of Jorge Lizama. GHD
    3 points
  2. Introduction IoT engineers need the ability to think at a systems level, and acquire cross-domain skills across engineering, business and application sectors. The main technical skill domains for IoT can be simplified to sensors and embedded systems, data analytics and integration, security, and IoT platform interoperability. To commercialise IoT solutions through startups or other commercial structures, business planning and innovation skills are also important. Having skills that span business engineering and multiple application areas can be very useful for IoT engineers, bus
    1 point
  3. Introduction Energy harvesting, also known as power scavenging, is the term used to describe methods for powering IoT devices from its local environment, rather than by mains power or primary batteries. The main sources of environmental power are photovoltaic, thermoelectric, kinetic, and radio frequency. These are complement by energy harvesting and power storage systems. A key misconception is that people equate power scavenging with perpetual life, that device will run forever. However, all systems have limitations. For example, a rechargeable cell powered by a solar panel will di
    1 point
  4. Introduction An IoT startup is a technically-lead small business that typically has yet to define its business model. Startups usually try several different routes to market prior to settling on an approach that has a good market fit. A key early goal for IoT startups is to identify the problem that is being solved by the use of IoT technology. The problem also has to be big enough for organisations to justify investing in a solution. Once a problem has been identified, the startup describes their hypothesis and identifies assumptions and risks. The next phase is to plan and te
    1 point
  5. The spectrum of technologies that enable IOT include advanced electronics and sensor/actuator technologies, next generation communication networks, cloud services to store the massive proliferation of data, big data analytics to make sense of it, mobile app development to interface with it and a whole range of protocols to enable it all to work together.
    1 point
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