“Cisco (NYSE: CSCO) and IBM (NYSE: IBM)
today announced a global collaboration to provide instant Internet of Things (IoT) insight at the edge of the network. Now, businesses and organizations
in remote and autonomous locations will be able to tap the combined power of IBM’s Watson IoT and business analytics technologies and Cisco’s edge analytics capabilities to more deeply understand and act on critical data on the network edge.”
IBM further describes its relations with Cisco:“Cisco and IBM have had a strategic alliance for more than 15 years. Together we have a “360 degree”
relationship; we use each other’s technology, we resell each other’s technology and we jointly sell the combination of our technologies together
in solutions… It is not an exclusive approach; however, our companies are fully committed to the success of this technology collaboration from
every aspect. To bring this solution to market and address the most critical needs of our customers, we are both offering pre-integrated and verified/interoperable
solutions.”
Key Insights:
- There is a low value-density in IoT data – e.g., getting oil pressure readings from a truck engine 1,000 times a second is not very helpful and
not worth the bandwidth or storage space in the cloud. - Network quality can reduce the value of IoT data.
- There is low time-value of IoT data – e.g., if you know the current pressure the previous 999 readings are not that valuable.
- If properly filtered and managed, there are opportunities to use IoT data to provide new (and hopefully) better approaches to controlling machines
and processes. - Industries that generate IoT and could benefit from IoT based controls and predictive analysis include:
- Transportation, trucking, shipping: dispatch, location, delivery time, schedule management, route management, equipment monitoring, safety
- Manufacturing: equipment monitoring
- Construction: equipment monitoring, safety
- Energy: oil rig management, power grid management, oil reservoir management
- Remote resource monitoring: forests, mines
- Restaurants: energy management
- Racing Boats: engine monitoring
My thoughts:
Engine oil pressure and getting the person out of the loop: At one point vehicles had oil pressure gages on the dashboard or that the operator could
monitor the pressure in real time and supposedly identify loss of pressure ahead of time. The gages were replaced by “idiot lights” that warned
the operator when the oil pressure was too low. IoT solutions suggest that we send the oil pressure data to a central “cloud” to determine when
the oil pressure is becoming a problem and issue orders to correct it. What is mainly changing in this sequence is the responsibility placed on
the operator (i.e. a person) to identify and do something about a problem with the oil pressure. This makes the most sense in cases where:
- The organization has a large number of vehicles and either cannot find or does not want to pay for competent operators.
- The overall number of sensors that must be monitored is too great for an operator to effectively manage.
Another issue with tracking the oil pressure is: Where should the analysis be done? Can an onboard computer watch the oil pressure over time and simply
issue a call to management that there is a problem, or is it better to only filter the data on board and send the results to the cloud for analysis?
If the goals are limited to finding oil leaks and scheduling maintenance then the onboard solution will win out as equipment vendors will use the
technology to upgrade their products. If the goal is to identify underlying design, use, or maintenance issues then a cloud solution is required
to track multiple devices over time periods greater that those between oil changes.
A philosophical note: People often prefer to deal with machines rather than other people. All things being equal would you prefer to use an ATM or
see a bank teller? Current advances in AI, IoT, mobile device communications, and so on are bringing on a new age in social interactions but also
the potential for a new age of social avoidance.