Cisco has leap frogged the Internet of Things (IoT) with its all-encompassing abstraction which it calls the Internet of Everything (IoE). As per Dave Evans, the Futurist of Cisco, IoE technically differs from the Internet of Things (IoT) in that IoE encompasses the networks that must support all the data that (IoT) objects generate and transmit, while (IoT) is composed of connected objects only. Software and the objects at the edge by themselves do not get the job done; the entire ecosystem is required to make a meaningful business model.
Cisco further differentiates its definition of the Internet of Everything (IoE) as bringing together people, process, data, and things to make networked connections more relevant and valuable than ever before-turning information into actions that create new capabilities, richer experiences, and unprecedented economic opportunity for businesses, individuals, and countries.
This distinction represents one of the main ways the company has differentiated its software-defined networking strategy from those of its competitors. Connected, location-aware applications require more bandwidth, more intelligence on the edge of the network, new considerations for security and orchestration, and more cohesive, programmable infrastructure.
A common understanding needs to be arrived at before any real implementation can happen. Towards this, a first step has been taken as recently as this week by The Open Interconnect Consortium (OIC) and the Industrial Internet Consortium (IIC) by reaching an agreement focusing on the interoperability technology, as nothing can really be achieved unless universal standards are in place to standardize connections between disparate devices and systems that permeate the industry today. OIC currently has 50+ members, including Dell, HP, Siemens and Honeywell while IIC has 141 members including founding companies like AT&T, Cisco, IBM, GE and Intel.
Big Data platform’s ability to capture, store and process humongous data cheaply and then applying new analytics’ open source tools and statistical languages like R with built in machine learning algorithms will make analysis available in real or near real time. These new tech paradigms will get the right data to the right device at the right time and to the right person or machine to be able to make the right decision; even seemingly inane concepts like sensor-equipped garbage cans can produce billions of dollars in efficiency-based savings. In the case of smart trash bins, embedded sensors can reduce calls to waste management by allowing officials to see how full a can is, whether hazardous materials are inside, how pickup efforts can affect traffic patterns, and even whether a given garbage can's contents might contain a particularly offensive odor. These insights might not seem ground-breaking alone, but together, they add up to billions in savings.
The Smart grid, a project close to my heart as it could be an extension to my already operational dream project of setting up the 5 MW Solar Photovoltaic plant in rural India to alleviate the energy deficiency in the Indian subcontinent and in strong personal belief in clean energy. Energy efficiency, Smart Grid and Smart city projects have been in the works for years but pervasiveness and effectiveness touted by IoE seems to be pulled from science fiction, such as humans who live to be hundreds of years old thanks to, among other things, personalized medicine and better collection of biometric data through wearable technology and sensor-embedded household objects.
In context of my 5 MW Solar PV project, we have 50,000 panels in the entire 40 acre farm with each panel made up of 60X72 solar PV cells which generates data points with regards to amperage and voltage ( among other parameters) every second. This translates into 216 million data points every second or 103 Billion data point every day (assuming an average of 8 hour sunlight). With IoE I can now predict power generation for the entire 25 years of the plant life on any given day of the year at a given geolocation, with certain ambient temperature, humidity and panel tilt angle. This information can be fed into the national Smart Grid in real time and thus the entire state or country’s energy cost and supply can be predictive well in advance based on historical data. Energy trading platforms, pricing and energy derivatives traders will really love this and so would consumers as they would benefit from the optimizing of power generation cost. Similarly, the IoE can be applied across all verticals in supply chain management of human consumption and personal health.
Cisco seems to have figured the right strategy and believes Internet of Everything (IoE) will alter the trajectory of virtually every person on the planet, consumer and professional alike, whether it's smarter power grids, personalized retail experiences, improved industrial efficiency, or the ability to control the infrastructure of an entire building with a smartphone app, IoE will be "bigger than anything that's ever been done in high tech. Cisco believes that by 2020 IoE revenues will touch $19 trillion!
I personally believe IoE is going to revolutionize and disrupt the way we humans have lived on this planet for millennia. In my short span of 25 years as a technocrat and a serial entrepreneur I have seem at least 4 disruptive technology cycles, however the disruption that will be caused by IoE in conjunction with Big Data, Analytics, Cognitive computing and Deep Learning will surpass all the earlier disruptions by more than 100 folds.
Originally posted on Data Science Central