Control Cube


Control Cube is a system (both software and hardware) developed by the research group of Associate Professor S. Nikoletseas. Control Cube enables conventional appliancies and automations to join the Internet of Things vision. By combining Future Internet Technologies (like IPv6, CoaAP and the IPSO Application Framework) and off-the-shelf electrical and electronic compontents into an open and modular architecture, Control Cube constitutes a low cost, easily deployable, plug-n-play solution that extends the IoT paradigm so as to also include legacy protocols and devices.

The Control Cube was selected as one of the 10 semi-finalists of the very competitive and international IPSO Challenge 2013. The 10 groups are:

  • Cisco Systems, Japan
  • Colorado Micro Devices, USA
  • FAST Laboratory (Tampere University of Technology), Finland
  • Oval Integration, USA
  • Purdue University, USA
  • Redwire Consulting, USA
  • University of Patras, Greece
  • University of Tokyo, Japan
  • viBrain Solutions and University of Murcia, Spain
  • Vienna University of Technology, Austria

Control Cube

The story has been covered by international press (The Wall Street Journal), major Greek press (To Vima, Kathimerini, Eleuterhotypia), Greek web portals (newsit, thebest, dete)


Detailed Description

Most commonly, when we refer to Smart Objects, we imagine of high tech devices that have been particularly engineered to natively support communication with the Internet. This way, however, myriads of legacy devices, that already exist and are already deployed all around us, are excluded from the Internet of Things vision.

In Smart Buildings, Smart Building Management Systems require that building appliances and devices (such as HVAC systems, lights and curtains) can be operated automatically either directly or via electromechanical actuators. However, in the case of old buildings, most commonly there is neither network cabling nor structured wiring and most devices are of legacy technologies with no networking interfaces. Standardizing the procedure of interfacing these devices with IoT-enabled sensor motes, that have wireless communication capabilities, would allow to create ad-hoc networks spanning across entire buildings without having the need to install any wiring infrastructure (thus leading to high cost savings). Furthermore, it would pave the way for already existing buildings to join the Internet of Things paradigm. In this context, Control Cube has already been successfully used in two experimental use case scenarios. First, an ordinary room has been turned into a smart one with minimal interventions, by interfacing few Control Cube prototypes to indoor light arrays, electric curtains, air-conditioning and ventilation units. By taking advantage of several Future Internet technologies, the room is able to adapt to human presence and the external environmental conditions, thus yielding significant energy savings.


While similar commercial solutions already exist, these are designed to operate as “black boxes”; they heavily rely on proprietary solutions that are vendor specific. Therefore, many interoperability issues arise, while the costs of purchase and maintenance are very high. The open and modular architecture of the Control Cube makes it vendor independent, thus allowing it to be interfaced with most of the already deployed devices, while maintaining its development and maintenance costs at low levels. Furthermore, it is highly customizable and upgradable so as to meet the specific needs of each application (e.g. if needed the weak TelosB platform can be easily replaced with a more powerful ARM microcontroller).

Control Cube is built around the well-known TelosB sensor mote platform. All other necessary parts are easily found as they are common electronic and electrical elements, such as AC/DC converters, mechanical relays, resistors, diodes, etc. However, during the development of the firmware of the Control Cube several technical hurdles have emerged. The CoAP implementation of TinyOS had to be greatly extended and adapted. New types of resources had to be implemented in order for the Control Cube to be able to drive as many devices as possible. At the same time, severe hardware limitations drove us to perform a careful resource optimization (mainly in terms of memory usage) when developing the firmware.


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