Sensors: Internet of Things (IOT) devices and systems include sensors that track and measure activity in the world. One example is Smartthings’ open-and-close sensors that detect whether or not a drawer, window, or door in your home is open or closed.
Connectivity: Internet connectivity is either contained in the item itself, or a connected hub, smartphone, or base station. If it's the latter, then the base station will likely be collecting data from an array of sensor-laden objects, and relaying data to the cloud and back.
Processors: Just like any computing device, IOT devices will contain some computing power “under the hood,” if only to be able to parse incoming data and transmit it.
Energy-efficiency: Many devices in the IOT may be difficult, costly, or dangerous to access for charging or battery replacement. One may even think of the Mars Curiosity Rover as an example of such a device. Therefore, they may need to be able to operate for a year or more unattended using a conservative amount of energy or be able to wake up only periodically to relay data.
Cost-effectiveness: Objects that contain sensors may need to be distributed broadly to be useful, as in the case of sensors in food products in supermarkets that would indicate if an item has spoiled. These would need to be relatively inexpensive to purchase and deploy.
Quality and reliability: Some IOT devices will need to operate in harsh environments outdoors and for extended periods of time.
Security: IOT devices may need to relay sensitive or regulated information such as health-related data, so data security will be critical.
You cannot improve and manage what you cannot measure.
Datification means we have more and more data to measure things and organizations are increasingly dependent on data - both internal and external - to optimally operate to compete and win. It is also about taking a process or activity that was previously invisible and turning it into data. That data can then be measured, tracked and monitored to optimize processes, make better decisions and innovate.
Sensors and devices (Internet of Things) will soon be embedded in all physical and biological things to collect data allowing organizations to better measure and improve performance. This will produce a massive volume and variety of data at unprecedented velocity. With sensors everywhere, from our cars and phones to roads and medical equipment, opportunities to collect data are endless. Combined with large scale analytics, new data driven business models are emerging, and are impacting all businesses, healthcare, city planning, public transportation, crime prevention and power utilization.
It is prudent for organizations to capture, store and analyze any and all information, even if they're not sure what insights the data will provide. Later the organization can decide what to look for to make better decisions on the operational level, innovate new products and services on the tactical level, and make game changing shifts on the strategic level.
Collecting and storing data from multiple sources - forming data science teams to combine, slice and dice this data to create valuable, actionable insights from the data - is the key to developing durable competitive advantage.
With sensors everywhere, from our cars and phones to roads and medical equipment, opportunities to collect data are endless. Combined with large scale analytics, new data driven business models are emerging, and are impacting healthcare, city planning, public transportation, crime prevention, power utilization, and local commerce.
This panel of experts will weigh in on the implications of this trend and examine the areas of greatest opportunity for innovation and business growth.
Rob Coneybeer, Managing Director, Shasta Ventures
Arna Ionescu, VP User Experience, Proteus Digital Health
Luc Julia, VP, Open Innovation Center, Samsung Electronics
Moderator: Craig McNeil, Managing Director, Accenture N. America Mobility
The Internet of Things (IOT) will soon produce a massive volume and variety of data at unprecedented velocity. If "Big Data" is the product of the IOT, "Data Science" is it's soul.
Let's define our terms:
Internet of Things (IOT): equipping all physical and organic things in the world with identifying intelligent devices allowing the near real-time collecting and sharing of data between machines and humans. The IOT era has already begun, albeit in it's first primitive stage.
Data Science: the analysis of data creation. May involve machine learning, algorithm design, computer science, modeling, statistics, analytics, math, artificial intelligence and business strategy.
Big Data: the collection, storage, analysis and distribution/access of large data sets. Usually includes data sets with sizes beyond the ability of standard software tools to capture, curate, manage, and process the data within a tolerable elapsed time.
We are in the pre-industrial age of data technology and science used to process and understand data. Yet the early evidence provides hope that we can manage and extract knowledge and wisdom from this data to improve life, business and public services at many levels.
To date, the internet has mostly connected people to information, people to people, and people to business. In the near future, the internet will provide organizations with unprecedented data. The IOT will create an open, global network that connects people, data and machines.
Billions of machines, products and things from the physical and organic world will merge with the digital world allowing near real-time connectivity and analysis. Machines and products (and every physical and organic thing) embedded with sensors and software - connected to other machines, networked systems, and to humans - allows us to cheaply and automatically collect and share data, analyze it and find valuable meaning. Machines and products in the future will have the intelligence to deliver the right information to the right people (or other intelligent machines and networks), any time, to any device. When smart machines and products can communicate, they help us and other machines understand so we can make better decisions, act fast, save time and money, and improve products and services.
The IOT, Data Science and Big Data will combine to create a revolution in the way organizations use technology and processes to collect, store, analyze and distribute any and all data required to operate optimally, improve products and services, save money and increase revenues. Simply put, welcome to the new information age, where we have the potential to radically improve human life (or create a dystopia - a subject for another time).
The IOT will produce gigantic amounts of data. Yet data alone is useless - it needs to be interpreted and turned into information. However, most information has limited value - it needs to be analyzed and turned into knowledge. Knowledge may have varying degrees of value - but it needs specialized manipulation to transform into valuable, actionable insights. Valuable, actionable knowledge has great value for specific domains and actions - yet requires sophisticated, specialized expertise to be transformed into multi-domain, cross-functional wisdom for game changing strategies and durable competitive advantage.
Big data may provide the operating system and special tools to get actionable value out of data, but the soul of the data, the knowledge and wisdom, is the bailiwick of the data scientist.