FORGE Course


Full Height |  Two columns |  Parts | 

Analytics over IoT data streams

Analytics over IoT data streams University of Ioannina 12/08/2016 English
Internet of things IoT cloud computing analytics

This course focuses on three thematic areas shown in the left hand side of the diagram below

  • IoT platforms (denoted as "IoTSTREAMS Widget")
  • Cloud-based IoT stream management (denoted as "IoTSTREAMS-cloud Widget")
  • IoT stream analytics (denoted as "Analytics Widget")

The right hand side of the diagram shows the associated middleware and infrastructures supporting the IoTSTREAMS course.

Note: To be able to read instructions-of-use alongside the Widgets you are experimenting with, it is advisable to use the two-column view, if your device and browser supports it.

Material on each thematic area consists of two parts, presentation and interaction (experimentation) with the underlying systems.

Within the interactive parts, the learner will go through (indicatively):

  • Exploration of system capabilities
  • Execution of basic functions 
  • Creation of specific interactions (selection of specific IoT nodes, configuration of data stream analytics, etc.)

The underlying systems used for experimentation in this course are located far apart geographically-- the IoT platform is based in Ioannina, Greece; the cloud infrastructure hosting the stream management middleware is based in Ghent, Belgium; the learner may be located anywhere in the world.

The geographical distribution of the experimental setup reflects real requirements of IoT applications: data analysis may need to take place far away from the area where the sensors are located, requiring the transportation of stream data over the Internet. The use of cloud-based middleware for stream management offers scalable stream management (the ability to allocate and use additional resources on demand) and the need for interoperability to bridge across a heterogeneous space of IoT devices.

Learning objectives

After completing this course, a student should be able to

  • Understand basic concepts of the Internet of things
  • Understand basic concepts of cloud-driven stream management middleware
  • Express basic real-time stream processing analytics using the Node-RED visual tool
  • Experiment further with more complex analytics over the IoT streams


This is a prototype course developed within the context of the FORGE EU project. While all effort was made to ensure that a large number of simultaneous learners can be accommodated, resource constraints in the underlying platforms may pose practical limits at times. Instructors planning to use this course as part of their course curriculum are welcome to get in touch with the course developers for capacity planning purposes.

IoT platforms (presentation)

IoT platforms (presentation) Department of Computer Science and Engineering, University of Ioannina 12/08/2016 English
Internet of Things IoT cloud computing analytics

We start with an introduction to basic notions of the Internet of Things.

According to the ITU, the Internet of Things (IoT) is the network of physical devices, vehicles, buildings and other items—embedded with electronics, software, sensors, and network connectivity that enables these objects to collect and exchange data. IoT devices are expected to generate large amounts of data from diverse locations, raising the need to aggregate, index, store,and process such data effectively.

The following picture (courtesy of a European Commission page on the Internet of Things) provides a figurative view of concepts connected to the IoT universe.

In recent years, the potential of the IoT to improve people's lives has elevated it to a key policy objective of many governments and organizations.  For example, the IoT has been a strategic direction in the EU Agenda for some time and the European Commission (EC) has been cooperating actively with EU member states and third countries towards the development and future deployment of the IoT technology. A key EC goal is to create a European Single market for a human-centered IoT and invests in fostering an innovative IoT ecosystem.

The following video from the IBM Think Academy provides a nice exposition of the key concepts underlying the Internet of Things:

A recent (2016) Ericsson mobility report (pdf) estimates that 1.5 billion IoT devices will be interconnected through cellular subscriptions by 2021. Within the IoT space,two major market segments with different requirements are emerging:

  • Massive applications, characterized by high connection volumes, low cost, requirements on low energy consumption and small data traffic volumes. Examples include smart buildings, transport logistics, fleet management smart meters and agriculture.
  • Critical applications, characterized by extremely high reliability and availability coupled with very low latency. Examples include traffic safety, autonomous cars, industrial applications, remote manufacturing and healthcare.

Now let's go over some key concepts within the IoT ecosystem:

IoT devices are typically embedded computing systems interconnected via a wireless networking technology so as to support dynamic self-organization of their communication infrastructure under arbitrary physical placements. The dominant wireless networking technologies today include Wi-Fi (based on the IEEE 802.11 family of standards), Bluetooth (previously standardized as IEEE 802.15.1 but currently controlled by the Bluetooth SIG), and ZigBee (based on the IEEE802.15.4 standard). More information about wireless networking technologies can be found here.

IoT devices typically combine wireless networking capability, limited processing capacity, and one or more sensors. Sensors are devices that allow for the retrieval of data from the environment around them, such as temperature, moisture, airflow, as well as other types of data such as position, etc.

An instance of the IoT devices deployed at the UoI testbed is shown below: