Innovations in Comfort, Efficiency, and Safety Solutions.
Irresistible Data Forces and Unmovable Buildings
Agents for the human and for the building will need to negotiate to come up with the best outcomes.
month’s magazine developed Ken Sinclair’s vision described of
Humanistic Digital Inclusion. This compelling vision will require
agents on the Internet of Things (including buildings) that are able to
anticipate the needs and wants of people and marshal the services to
provide them. This will create a premium around local knowledge as each
building, and each environment has hard local requirements. For
example, a building that has been allowed to grow too warm in the
summer may be unable to cool on demand to the target temperature
required by the human-centered agent. Agents for the human and for the
building will need to negotiate to come up with the best outcomes.
It is a mistake to think that our
current application paradigms, always driven by the last big problem,
will be how this comes together. Today, we imagine all that all
applications must be cloud-based because we live on the internet and
get so much wonderful content for free. Somehow real monetization will
flow from things we learn across all platforms, just as today, real
wealth falls out of web tracking and advertising. Others hope they will
find value in huge masses of data, just as the cheap gene sequencers
(23&Me et al.) give away services as a means to someday own
personal actuarial data to sell to financial services companies.
What cannot go on forever, though, must stop someday.
This month, the first tangible wave of
the global revulsion against this model rolls out, and websites
everywhere are asking for permission to track under the new rules. In
the US, the data harvesters such as FaceBook and Cambridge Analytica
have been chastised by many who while complacent when data harvesting
supported purposes they approved of, are now horrified that the same
data and same techniques can also support purposes they disagree with.
In buildings and physical
infrastructure, the new value propositions in IoT-based services are
most valuable where they cannot be used with today’s techniques.
Tracking and sharing of Fit-Bit data have put at risk military and
security operations worldwide. Highly structured operations in critical
pharmaceutical manufacturing facilities become easier targets for
disruption as operational data leaks into the world. Easy remote access
becomes more and more security risk. Smart transactive microgrids can
create needed resilience for high-value facilities, but if cloud-based,
are poor fits for facilities that wish to cloak their electrical use to
occlude power signatures.
For the most critical resources, the
communications channel itself becomes the Secure networks have been
compromised as individual smart lightbulbs and thermostats become
targets to enter entire secure networks at will. Loss or interruption
of connectivity, whether through equipment failure or through line
interruption, whether from natural causes or from enemy action, becomes
unacceptable as the criticality of the systems increases.
The work of IT Architect Pat Helland has
long provided useful models for thinking of this sort of change. His
landmark 2004 article “Metropolis” on real-world technology evolution
should be read by anyone contemplating large-scale multi-system
multi-vendor build-outs. He outlined the challenges of widely
distributed data and diverse distributed processing in the talk “The Irresistible Forces meet the Immoveable Objects”
in 2007, which addressed the issues only now coming to the fore. More
recently, Helland has written on the importance of immutable data for
new systems, and even that data immutability is more important than
Data Immutability can be understood as
the principle that once written, data is never changed. If the data is
signed, the signature is verified, and the signature cannot be changed.
By analogy, data immutability is the accounting principle that ledger
entries are written in ink. Entries can be backed out with a new entry,
but never deleted.
Nowhere is data immutability more
important than when AI (Artificial Intelligence) is applied to the IoT.
Operational AI finds patterns in how things work and then uses those
patterns to make things work better. Even the most secure AI Agents can
be co-opted by feeding them bad data that will create incorrect
patterns. Incorrect patterns can induce behaviors whose effects can
range from merely disruptive to financially expensive to imminent
dangers to health and safety.
Cloud-based systems create data
immutability by managing data on traditional databases that are managed
in the cloud. Professionals manage data back-up, and whoever can see
that data can see all data. Loss of access to the data is as harmful as
loss of connectivity to the cloud.
With traditional databases, local data
storage becomes a risk. Bad data can be introduced locally into the
database using common tools. Local databases must be backed up and
managed just as professionally as the ones in the cloud are.
is a term that encompasses the techniques used in cryptocurrencies such
as BitCoin and Ethereum. Cryptoassets use specialized hashing
algorithms to create distributed immutable databases. When these
databases have a local scope, with no need for universal access and
scale, these databases can be built using small, inexpensive systems
such as the Raspberry Pi. Just as a disk RAID set can lose a member and
still retrieve all data, so can a hashed distributed database a member
and still have the entire dataset.
New systems can be introduced to and
begin participating in such a system. Other agents, with appropriate
authorization, can be permitted to read all or part of this immutable
database. The system can share access to operational data with third
parties, such as a utility or accrediting agency, that pays for access
and trusts this database does not need to upload data constantly.
Operational AI-based Agents can interact with such databases with
For years, I have described the imminent
arrival of small system-based AI in smart buildings. Last summer,
Microsoft released an open-source GitHub of AI for small systems
including the Raspberry Pi. Last month, Alper Üzmezler revealed his
SandStar platform for autonomous building control components. Couple
these with an immutable database to support the AI and the components
for real learning-based building systems are in place.
Such AI systems will be needed to fully
embrace Ken’s vision of Humanistic Digital Inclusion. The larger
database can learn about individuals within a building and pass hints
to each system. Those systems can store new information about
preferences in the building-wide immutable database. The remaining
question is how one building can tell a peer what the human likes or
wants. That will be an interesting set of standards to watch develop.
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