IEEE Systems, Man and Cybernetics Magazine - October 2020 - 36

databases and complex event processing can be useful in
this context. The IoT could reduce the need to manually
signify the completion of tasks since sensor data would
already be available, leading to more accurate information, fewer errors, and efficiency gains.
To provide guidelines for system development, several
challenges remain to be tackled. In particular, the following issues must be understood:
◆ how processes can improve the IoT by 1) taking a process-oriented perspective and considering the process
history to 2) bridge the abstraction gap between raw
sensor data and higher-level knowledge extracted from
that event data and 3) optimize the overall decision
making
◆ how to exploit the IoT for BPM by 1) considering sensor data for automatically detecting the start and end
of activities, 2) using event data for making decisions
in a predefined process model, and 3) detecting

Business Process Management
Business process management (BPM) is a well-established
discipline that deals with the identification, discovery,
analysis, (re)design, implementation, execution, monitoring,
and evolution of organizational procedures [S5]. A business
process is a collection of related events, activities, and
decisions that involves a number of actors and resources
and that leads to an outcome that is of value for an
organization or customer. Examples of business processes
include order to cash, procure to pay, application to
approval, claim to settlement, and fault to resolution.
To support business processes at an operational level, a
BPM system (BPMS) can be used. As opposed to data- and
function-centered information systems, a BPMS separates
process logic from application code and thus provides
an additional architectural layer. Typically, a BPMS provides
generic services that are necessary for operational,
software-enabled business process support, i.e., for
process modeling, execution, and monitoring and for user

The Internet of Things

interaction (e.g., worklist management). When using a

The Internet of Things (IoT) [5], [S1], [S2] is the

BPMS, software-enabled business processes are designed

internetworking of physical objects (the things), such as

in a top-down manner; i.e., process logic is explicitly

embedded systems with electronics hardware, software,

described in terms of a process model that provides the

sensors, actuators, and network connectivity. Such

schema for the process execution. The BPMS is responsible

connected things collect and exchange data. Each

for instantiating new process instances, controlling their

thing is uniquely identifiable through its embedded

execution based on the model, and completing them.

computing system and is able to interoperate within the

The progress of a process instance is typically monitored,

existing network infrastructure. While things act locally,

and traces of the execution are stored in an event log and

the IoT enables them to be controlled remotely across

can be used for process mining [S6], e.g., the discovery of

existing network infrastructures, including the Internet.

a process model from the event log and for checking the

The interconnection of these smart objects/things [S3]

compliance of the log with a given process model.

is expected to usher in automation in nearly all fields.

So far, the predominant paradigm to develop

This creates opportunities for more direct integration of

operational support for business processes has been

the physical world into computer-based and digitized

based on the model-enact paradigm, where the system

systems and results in improved efficiency, accuracy, and

has been depicted as a (graphical) model that then

economic benefits as well as increased automation and

could be executed by a BPMS. This largely follows a top-

less human intervention. Experts estimate that the IoT will

down approach and is based on the idea of a central

consist of roughly 30 billion objects in 2020 [S4].

orchestrator that controls the execution of the business
process, its data, and its resources. With the emergence of

References

the Internet of Things, the existing model-enact paradigm

[S1] K. Ashton et al., "That 'Internet of Things' thing," RFID J., vol. 22,

is challenged by the discover-predict architecture, which

no. 7, pp. 97-114, 2009.

can be characterized as a bottom-up approach where

[S2] J. Holler, V. Tsiatsis, C. Mulligan, S. Avesand, S. Karnouskos, and

data are generated from physical devices that sense their

D. Boyle, From Machine-to-Machine to the Internet of Things: Intro-

environment and produce raw events. Sensor data then

duction to a New Age of Intelligence. New York: Academic, 2014.

must be aggregated and interpreted to detect activities

[S3] G. Kortuem, F. Kawsar, V. Sundramoorthy, and D. Fitton, "Smart

that can be used as input for process mining algorithms

objects as building blocks for the Internet of Things," IEEE Inter-

that support decision making.

net Comput., vol. 14, no. 1, pp. 44-51, Jan. 2010. doi: 10.1109/
MIC.2009.143.

36

References

[S4] A. Nordrum "Popular Internet of Things forecast of 50 billion

[S5] M. Dumas, M. La Rosa, J. Mendling, and H. A. Reijers , Funda-

devices by 2020 is outdated," IEEE Spectrum Tech Talk, Aug. 18, 2016.

mentals of Business Process Management, 2nd ed. Berlin: Springer-

[Online]. Available: https://spectrum.ieee.org/tech-talk/telecom/

Verlag, 2018.

internet/popular-internet-of-things-forecast-of-50-billion-devices

[S6] W. Van Der Aalst, Process Mining: Discovery, Conformance and

-by-2020-is-outdated

Enhancement of Business Processes, 2nd ed. Berlin: Springer-Verlag, 2016.

IEEE SYSTEMS, MAN, & CYBERNETICS MAGAZINE O ctober 2020


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IEEE Systems, Man and Cybernetics Magazine - October 2020

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