These are unprecedented times. The world hadn’t witnessed
such a disruption in recent history. It is times like these test the strength
and resilience of our community. While we’ve been advised to maintain social
distancing to flatten to curve, we must keep the wheels of the economy rolling.
In my previous article, I covered the ‘People-Centric’ Tech
Trends of the year, i.e., Hyper automation, Multiexperience, Democratization,
Human Augmentation and Transparency and Traceability. All of those hold more
importance now in the light of current events. Per Gartner, Smart Spaces enable
people to interact with people-centric technologies. Hence, the next Tech
Trends in the list are about creating ‘Smart Spaces’ around us.
Smart spaces, in simple words, are interactive physical
environments decked out with technology, that act as a bridge between humans
and the digital world. The most common example of a smart space is a smart
home, also called as a connected home. Other environments that could be a smart
space are offices and communal workspaces; hotels, malls, hospitals, public places
such as libraries and schools, and transportation portals such as airports and
train stations. Listed below are the 5 Smart Spaces Technology Trends which,
per Gartner, have great potential for disruption.
Edge computing is a distributed computing topology in which
information processing and data storage are located closer to the sources,
repositories and consumers of this information. Empowered Edge is about moving
towards a smarter, faster and more flexible edge by using more adaptive
processes, fog/mesh architectures, dynamic network topology and distributed
cloud. This trend will be introduced across a spectrum of endpoint devices
which includes simple embedded devices (e.g., appliances, industrial devices),
input/output devices (e.g., speakers, screens), computing devices (e.g.,
smartphones, PCs) and complex embedded devices (e.g., automobiles, power
generators). Per Gartner predictions, by 2022, more than 50% of
enterprise-generated data will be created and processed outside the data center
or cloud. This trend also includes the next-generation cellular standard after
4G Long Term Evolution (LTE), i.e., 5G. The concept of edge also percolates to
the digital-twin models.
Gartner defines a distributed cloud as “distribution of public cloud services to different locations outside
the cloud providers’ data centers, while the originating public cloud provider
assumes responsibility for the operation, governance, maintenance and updates.” Cloud computing has always been viewed as a centralized service, although,
private and hybrid cloud options compliments this model. Implementing private
cloud is not an easy task and hybrid cloud breaks many important cloud
computing principles such as shifting the responsibility to cloud providers,
exploiting the economics of cloud elasticity and using the top-class services
of large cloud service providers. A distributed cloud provides services in a
location which meets organization’s requirements without compromising on the
features of a public cloud. This trend is still in the early stages of
development and is expected to build in three phases:
Phase 1: Services will be provided from a micro-cloud which
will have a subset of services from its centralized cloud.
Phase 2: An extension to phase 1, where service provider will
team up with a third-party to deliver subset of services from the centralized
Phase 3: Distributed cloud substations will be setup which
could be shared by different organizations. This will improve the economics
associated as the installation cost can be split among the companies.
Autonomous can be defined as being able to control oneself.
Similarly, Autonomous Things are devices which can operate by themselves
without human intervention using AI to automate all their functions. The most
common among these devices are robots, drones, and aircrafts. These devices can
operate across different environments and will interact more naturally with
their surroundings and people. While exploring use cases of this technology,
understanding the different spaces the device will interact to, is very
important like the people, terrain obstacles or other autonomous things.
Another aspect to consider would be the level of autonomy which can be applied.
The different levels are: No automation, Human-assisted automation, Partial
automation, Conditional automation, High automation and Full automation. With
the proliferation of this trend, a shift is expected from stand-alone
intelligent things to collaborative intelligent things in which multiple
devices work together to deliver the final output. The U.S. Defense Advanced
Research Projects Agency (DARPA) is studying the use of drone swarms to defend
or attack military targets.
Most of us have heard about Blockchain technology. It is a
tamper-proof, decentralized, distributed database that stores blocks of records
linked together using cryptography. It holds the power to take industries to
another level by enabling trust, providing transparency, reducing transaction
settlement times and improving cash flow. Blockchain also makes it easy to
trail assets back to its origin, reducing the chances of substituting it with
counterfeit products. Smart contracts are used as part of the blockchain which
can trigger actions on encountering any change in the blockchain; such as
releasing payment when goods are received. New developments are being
introduced in public blockchains but over time these will be integrated with
permissioned blockchains which supports membership, governance and operating
model requirements. Some of the use cases of this trend that Gartner has
identified are: Asset Tracking, Identity Management/Know Your Client (KYC), Internal
Record Keeping, Shared Record Keeping, Smart Cities/the IoT, Trading,
Blockchain-based voting, Cryptocurrency payments and remittance services. Per
the 2019 Gartner CIO Survey, in the next three years 60% of CIOs expect
blockchain deployment in some way.
Per Gartner, over the next five years AI-based decision-making
will be applied across a wide set of use cases which will result in a
tremendous increase of potential attack surfaces. Gartner provides three key
perspectives on how AI impacts security: protecting AI-powered systems, leveraging
AI to enhance security defense and anticipating negative use of AI by
attackers. ML pipelines have different phases and at each of these phases there
are various kinds of risks associated. AI-based security tools can be very
powerful extension to toolkits with use cases such as security monitoring,
malware detection, etc. On the other hand, there are many AI-related attack
techniques which include training data poisoning, adversarial inputs and model
theft and per Gartner predictions, through 2022, 30% of all AI cyberattacks
will leverage these attacking techniques. Every innovation in AI can be
exploited by attackers for finding new vulnerabilities. Few of the AI attacks
that security professionals must explore are phishing, identity theft and
One of the
most important things to note here is that the trends listed above cannot exist
in isolation. IT leaders must analyse what combination of these trends will
drive the most innovation and strategy fitting it into their business models.
Soon we will have smart spaces around us in forms of factories, offices and
cities with increasingly insightful digital services everywhere for an ambient
About the Author:
Priyanka is an ardent feminist and a dog-lover. She spends her free time cooking, reading poetry and exploring new ways to conserve the environment.