A Unified Data Platform for IoT transport protocol interoperability, part four – Automated analytics

 

This multi-part series addresses the need for a single data interoperability model that unifies data exchange across multiple transport protocols (including SMTP, MQTT, CoAP, DDS, BACnet, and others) via an extension layer. Such a layer must be simple and extensible to enable plug and play interoperability and universal adoption amongst humans, machines, and applications in the IoT.

Editor’s note: Read part three, “Universal runtime for software-defined machines” at iotdesign.embedded-computing.com/articles/a-unified-data-platform-for-iot-transport-protocol-interoperability-part-three-universal-runtime-for-portable-apps-frameworks.

Automated analytics can leverage historical object events to provide anticipatory digital life experiences.[11] An analytics engine can filter this history, find patterns, predict future scenarios, and automatically insert these insights into system and machine processes that anticipate, direct, and engage consumers.

For example, a history of object events maintained in a data store can be filtered by a machine’s analytics engine to establish a pattern of brewing times that were manually initiated by Alice (Figure 30). From the pattern, the analytics engine can generate object events that create a Trigger and Action to automatically initiate coffee brewing at a set time. When processed by a runtime, these object events can generate new Trigger and Action objects (Figure 18) that can be included in a portable app update on the coffee machine.

Figure 30

Every app now needs to be an analytic app. Organizations need to manage how best to filter the huge amounts of data coming from the Internet of Things (IoT), social media, and wearable devices, and then deliver exactly the right information, to the right person, at the right time. Analytics will become deeply, but invisibly, embedded everywhere.[12]

Universal human-to-machine-to-machine communications

Automated analytics, software-defined machines, and on-demand apps can all be wrapped up into one seamless, unified data platform based on an all-encompassing, entity-relationship metadata model. A new collaborative technology can be the mid-way between the informality of email and the rigidity of purpose-built, proprietary apps and systems. Email and other ad hoc collaboration systems are typically lightweight and flexible, but build up an unmanageable clutter of copied objects. An “object-centric, peer-to-peer sharing” technology can promote lightweight, structured communications with dynamic membership, hierarchical object relationships, as well as real-time and asynchronous collaboration.[13]

A simple, universal data infrastructure can standardize create, read, update, and delete (CRUD) operations between humans and all types of connected machines (including mobile and embedded devices, gateways, and cloud servers) within a peer-to-peer network (Figure 31). These interoperable machines can simultaneously function as both “clients” and “servers” to other connected machines through a single data service (BEAM Service) based on a unified message payload protocol (BEAM Protocol). These services can exchange semantically precise, serialized datasets as message payloads that contain object events, query requests, and view responses. Message payloads can support CRUD operations for any digital object, from a data-defined machine or email message to a metadata-defined attribute of a “Machine” and “Message” entity.

Figure 31

The data service’s universal runtime can process inbound message payloads to load portable apps and frameworks, update data stores, and generate outbound message payloads from triggered actions. These outbound payloads can be processed by other machine resources (like a rendering engine, print engine, or mechanism) or transported to other machines for processing.

A Unified Data Platform can provide seamless information exchange between humans and machines, and enable machines to work together to form interoperable automation systems, providing the ultimate consumer experience.

The ultimate consumer shopping experience

What if a consumer’s interaction with a retailer, from start to finish, went exactly the way the consumer would like it to? Omnichannel is about true continuity of the consumer’s shopping experience. But what’s key is that it extends beyond a single retailer or brand. The ability to have a continuous experience across brands, across format, and across devices that is completely bespoke– that’s the ultimate consumer shopping experience.[14]

The omnichannel retail revolution is gathering pace and its effect is going to be transformative. Mall owners and their retailers must invest in new technologies and digital strategies to reshape the physical shopping experience. Unless completely reinvented, the shopping mall will become a “historical anachronism — a sixty-year aberration that no longer meets the public’s needs.”[15] The shopping malls that can provide the most immersive, exciting, and attentive services are the ones that will thrive.

By standardizing on a Data Platform that unifies commerce, devices, and events (Figure 32), interoperable retail automation systems can provide the consumer with a continuum of contextual digital life experiences that anticipate, direct, and engage.

[Figure 32]

Transport protocols (like SMTP, MQTT, CoAP, and AMQP) can provide an extension layer that supports a unified message payload format.

A consumer’s smartphone, a mall’s automated car parking attendant, and a retailer’s inventory management system can work together to communicate state changes, trigger actions, and render contextual, actionable user interfaces.

Consumers, store attendants, mall owners, and retailers can share information through domain memberships defined in data stores. A car’s plate number, a gate’s status, an item’s size, a customer’s birthday, and a store item’s quantity can be defined as entity attributes within the same data stores.

Automated analytics can generate triggers that increase customer retention, such as WHEN “Visits” of Customer is 10, THEN “Status” of Gate is open; and WHEN “Birthday” of Customer is today, THEN Create Task for store attendant.

Let’s say you drive to a mall for a day’s shopping:

An automated car parking attendant scans your license plate number. A triggered action sends an object event containing the plate number in a message to a gateway. A triggered action on the gateway generates an object query that’s executed by the gateway’s data store engine. The engine retrieves the “Visits” attribute value of the customer associated with the plate number. The retrieved value of 10 triggers another action on the gateway that sends an object event in a message to the automated car parking attendant to change the “Status” of its gate to Open.

As you enter the mall, your smartphone connects to the mall’s Wi-Fi network (Figure 33). This triggers an action that sends your smartphone’s MAC address within an object event in a message to the gateway. Triggered actions on the gateway generate object events that are processed by its data store engine to create a connection and session object. Another triggered action sends the mall’s portable app as an object view in a message to your smartphone, which renders the app on its screen. Store offers appear as email messages within the app.

As you near the entrance of a store, your smartphone connects to its Wi-Fi network, which sends the store’s portable app to your smartphone and generates an object query to retrieve the “Birthday” attribute value of the customer associated with your smartphone’s MAC address. The retrieved value matching today’s date triggers an action on the retailer’s cloud server. The server sends object events representing a new Task in a message to a store attendant’s smartphone, which renders the task alert on its screen. The store attendant hurries over with a glass of champagne.

A time-triggered action can synchronize customer objects within the mall’s gateway and cloud server data stores by exchanging messages containing omnichannel object events.

Conclusion

Transforming mobile email into the ultimate consumer experience is only possible if machines and systems can interoperate without complex system integrations and message translations. Interoperable automation requires a simple, universal data infrastructure for human-to-machine-to-machine communications that is sustainable for decades.

Standardizing the interoperation within one system is not adequate. A single unifying standard must be developed that can span all machines, systems, and applications that affect a consumer experience, from parking and store automation to warehouse and home automation; from human-to-machine interfaces to machine-to-machine communications; from mobile email to the Internet of Things.

This requires normalizing data to a common denominator and transitioning from human-readable code to machine-readable metadata; from purpose-built apps run on universal machines to universal apps run on purpose-built machines; from SMTP to a Unified Data Platform.

A Unified Data Platform based on an entity-relationship metadata model can significantly reduce the time, cost, and risk required of mall owners, retailers, and manufacturers to build this sustainable ecosystem of interoperable automation.

Doug Migliori is President of ControlBEAM Digital Automation.

ControlBEAM

www.controlbeam.com

automate@controlbeam.com

For related discussions, join the IoT in Retail group on LinkedIn: www.linkedin.com/groups/7035079

References

11. The Rise of Automated Analytics, Tom Davenport, Wall Street Journal, January 2015

12. Top 10 Technology Trends for 2015, David Cearley, Gartner

13. Supporting Activity-centric Collaboration through Peer-to-Peer Shared Objects, Werner Geyer and Michael Muller, IBM Research, 2003

14. What is Omnichannel?, CloudTags, Inc. 2015

15. Rethinking Retail One Mall at a Time, Westfield Labs, Steven Jacobs, May 20, 2014