AWS IoT provides a managed, multitenant service that enables communication between IoT devices, applications, and the backend. By virtue of being a managed service, IoT platform eases out several deployment and infrastructure monitoring issues. However, it imposes some limits and restrictions on how data can be modeled and the size of device information that can be stored in a “shadow” on AWS IoT 1. Primarily, the restrictions ensure the safety and security of the platform and deployments, and avoid misuse of the platform by a tenant or rogue entity. It is critical to be aware of and understand these restrictions before finalizing the solution architecture as some of them may impact the feasibility of the solution architecture and operating costs.
IDC forecasts that the worldwide IoT market will grow from $655.8 billion in 2014 to $1.7 trillion in 2020, with a compound annual growth rate of 16.9%. This growth will be dominated by the manufacture of devices, and investment in connectivity and IT services. IDC also predicts purpose-built platforms, application software, and as-a-service offerings will capture a larger percentage of the market by 2020. While the IoT managed services market is estimated to grow from USD 21.85 billion in 2016 to USD 79.60 billion by 2021, at a compound annual growth rate of 29.5% during the period 2016–2021, according to a research by MarketsandMarkets research firm.
The moment you switch on a device, the expectation is there is absolutely no lag in display and output. Is this too much to ask for? Not anymore say experts. Many engineering companies, spending their valuable time and resources to develop solutions with shorter bootup time. With IoT being the center of all operations and various devices being operated simultaneously by one person at any given point of time, it becomes all the more imperative that all the devices and thus all the systems boot together and faster.
When the first publicly available web page was accessed on August 23, 1991, Tim Burners Lee’s greatest contribution to mankind triggered an avalanche of possibilities which after 26 years has become an indispensable part of our lives. Internet can be a synonym for connectivity but nothing justifies that proposition as much as Internet of Things (IoT).
Designing products and services to be frictionless will lead to more compelling user experiences and greater affinity with the customer. For example, biometric chip in Apple iPhone helps establish seamless user identity & trust to unlock screen, make one-step secure payment to buy apps from app store etc. In this case, there is a 1:1 relationship between user-device and manufacturer of a device enabling frictionless experience for user. But it is not the same in the case of an upscale hotel that has IoT devices (smart bulbs, digital key locks, smart thermostat, connected vending machines etc.) to enhance guest experience i.e., hotel first needs to secure different manufacturer’s IoT devices procured & installed in its premises and rooms. Then establish a temporary trust relationship between guest checking into the hotel & devices in room and when guest checks out remove the temporary trust established at the time of check-in to avoid misuse of devices by guests etc.
The S of IoT networks
The assumption about big data analytics is that if you capture more data and analyze, the more accurate your results will be. But it doesn’t matter how big your data volume is and how optimized and efficient your analytics algorithms are, if the analyzed data is inaccurate from the sources, then it will surely result into inaccurate analytics.