Guest post by Ted Konnerth, Egret Consulting
I was invited to join a panel at the new IoT Emerge conference in Chicago. As a lifelong industry guy who has grown up selling and marketing tangible products, it was an interesting and stimulating environment to be surrounded by tech guys who see the world through software solutions. One thing I learned… IoT is YUGE.
IoT is distinguished from IoP; i.e. Internet of People. The internet we’ve become reliant on was crafted for people; communications, information access, interacting; etc. As the keynote speaker Tim Chou emphasized… People are not Things. So the IoT is being crafted as a data communication system that is based upon the flow of information. Massive amounts of information, so much that there will soon be a requirement for a new category of information volume; Terabytes become useless when we begin to talk about trillions of Terabytes. So let’s review Mr. Chou’s overview:
Things are where people aren’t.
Things can do things faster than people.
Things can be programmed, people can’t.
The IoT is based on the premise that with increasing numbers of sensors, we will create massive amounts of data; which will require massive amounts of data analysis and storage and ideally… actionable and predictive assessments. So that leads to 4 steps in the development:
Sensor technology. Cell phones currently have 12 sensors and, at the current production levels of 100’s of millions of new cell phones, sensor design and costs are plummeting. With the drop in sensor cost, then the deployment of sensors will grow. Sensor tech is roughly adhering to Moore’s Law, and there are hundreds of sensors, with many more to come.
With massive growth in sensor applications there will be growth in communication networks to handle the data surge.
The pace of data generation is exploding. As an example, a typical oil rig has over 40,000 sensors on it. Wind turbine farms can generate over 1,000 Terabytes/yr. Data collection systems have to expand proportional to the adoption of sensor applications.
With the amount of data being generated… how do you analyze and interpret that much data? The answer to this is Artificial Intelligence (AI). AI tech is at the core of machine learning and will also grow proportional to the data collection growth.
Why do machine makers care about data and IoT?
Quality of service and products will improve
Cost of service will drop and lead to new business models:
Service contracts. GE currently has approximately $50B/yr in service contracts ($70B in product sales)
Assisted services. As the machines ‘talk’ to their manufacturer, the manufacturer can offer advice and assistance to the operators or owners of the machines to improve performance.
Machine as a service. Manufacturers have already begun to lease their machines as part of a service contract, e.g.: sell tires at $/mile rate and change them as they age. Sell compressed air by leasing the equipment and maintaining those machines.
Drive down costs
Improve quality
Improve the environment, e.g. farmers can lease their equipment and modify their seeding operation based upon the condition of the soil and weather, and modify or minimize their pesticide or fertilizer usage.
Improve safety
Asset management
In short, the potential benefits of IoT adoption are enormous and will result in dramatically different approaches to business. But then there’s the downside:
Every speaker addressed security as a ‘concern’. But nobody said it will be solved soon. The advantage of the IoT is that this is a new paradigm, the chance to ‘invent the internet’ all over again. Hopefully the new internet will be far safer than the current one.
Technical issues: from standardized communication platforms (Zigbee, Bluetooth, WiFi, etc.), to vendor assessments, application development, pricing models and interoperability issues.. it’s going to take time to create the ‘new’ internet. And there will be winners and bad losers.
Channel players. Ahh, my favorite theme since SSL became ‘real’. IoT is amorphous, it requires hardware to work and the application and location of that hardware will lead to the channel players who can assist in its growth. And that leads us back to the electrical industry.
Our industry is poised as a leading participant in the development and launch of the IoT. Major manufacturers are already lining up to play in IoT; from auto manufacturers to GE, Cargill, Monsanto and Johnson and Johnson. The electrical industry has the infrastructure for energy: from T&D equipment to your bathroom light switch, there will be a favored geographical hegemony for our industry to harbor sensors. The bigger issue is who will influence the selection of electrical equipment, define the sensor technology and scope, and integrate that data transfer to a collection server for data analytics?
Electrical industry meets technology industry. It’s here. We all hope it’s collaborative and strategic to ensure that the right sensors are placed on the right equipment in a fashion that doesn’t impede the proper design and application of the original equipment. We don’t want Cisco engineers designing the lighting layout for the next art museum to optimize people movement analytics and temperature indicators to protect the artwork. And we really don’t want sensors on our T&D equipment being easily hacked and subsequently infecting the utility IT infrastructure.
We have huge opportunities ahead of us. The IoT will provide the shiniest object for many of the brightest engineers and scientists in the years ahead. Attracting leadership talent that understands the potential of the IoT and how to monetize investments in IoT will be a challenge. What kind of background would that leader have? Industry or tech? And the possibility of creating new business models that transcend the pure manufacture and sale of hard goods.. is exciting. We’re at a time in history that has never occurred before, let’s all figure out how to adapt.
