The MI test-beds. A first testbed has been deployed in MI Welcome Centre. For security reasons, MI had to close its Welcome Centre by the end of 2012. MI deployed two additional test beds in its research Lab at the University of Applied Sciences Western Switzerland, as well as in an office space near the UN with a meeting area and several work stations. Those two test beds will be maintained beyond the end of the HOBNET research project and will be used among others by the EAR-IT FP7 research project.
The testbeds have enabled MI to assess the technologies developed from an end-user perspective by implementing and testing 10 out of the 12 selected use cases. Here follow a summarized description of the test-bed deployment. More detailed description are available in the respective deliverables.
Sensors deployed at the MI testbed include: CO2, humidity, oil level, appliance status, door opening detection, presence detection, identification, energy consumption, window opening detection, water flow, seismic activity detection, soil moisture, light level, temperature, water leak, fire detection. Actuators deployed include: appliance switch, blind controller, heater controller, light dimmer, watering, electrical lock, air condition control. Other components include: exit lights, multimedia, access points, multiprotocol card, NFC reader, smart phones.
The CTI test-bed. Apart from the already existing smart room, CTI testbed has been scaled out to 21 motes deployed over 7 offices at the premises of our building. The motes are organized in a mesh topology and communicate with the main server of the testbed via multihop data propagation. We would like to note that several of these additional motes are running Contiki OS; therefore the testbed consists of sensor motes running both TinyOS and Contiki. The testbed has also been upgraded from CoAP-03 to CoAP-12 while additional virtual resources have been implemented (i.e. average/min/max temperature and humidity) that combine readings from multiple sensors in order to provide a more abstract piece of information.
Comparison to the state of the art protocols. Using the extended CTI testbed we have conducted research on our energy balanced RPL (EB-RPL) that was initially evaluated using the SenseWall testbed. This new set of experiments gave us the opportunity to evaluate EB-RPL under real operating conditions in a building environment (this includes obstacles such as walls, moving people, interference from other networks like WiFi and cellular). The experiments ran over a period of two months for each routing protocol. EB-RPL virtually partitions the network into five sectors (as shown in the Figure above) and each node of a sector either transmits directly to the sink or to a node in the next sector. As far as energy balance property is concerned, the main findings show that EB-RPL is more efficient than RPL, which tends to overuse nodes closer to the Sink, resulting to early network disconnections. This is due to the fact that nodes have limited transmission range and all traffic has to be served through the small number of nodes that lie closer to the sink. We note that RPL, even if it is a tree-like protocol, has an energy balancing mechanism, by supporting data propagation via alternative paths for each node to the sink. The next Figure depicts the energy dissipation of the two protocols. The upper part of the Figure shows the values of energy dissipation of each node by ID. The lower part shows the energy map of the network according to the virtual sector topology. Darker nodes are those with lower residual energy, whereas the brighter ones are those with more energy. Note that the energy dissipation was measured by the voltage difference of each mote’s battery supply. It is evident that the RPL-EBP protocol brings off the energy balance property, since there is a color uniformity over the network.
In order to achieve increased energy balance in the network, EB-RPL has to spend more energy. Nodes may sometimes transmit their data directly to the sink, by increasing their transmission range online, thus spending more energy on transmissions but achieving lower delivery latency. Long range transmissions, which are absent from RPL, require higher energy supplies, The next Figure depicts average energy consumption and data delivery rate for the two protocols.
Balance of the energy saving vs end-user comfort. We have conducted research on user comfort in buildings. We have thoroughly studied corresponding bibliography on the Sick Building Syndrome and the Air Quality Monitoring. We have also identified ways of quantifying the comfort an end-user receives while inside a building. For instance, the Predicted Mean Vote (PMV) averages human comfort over a large group considering six key factors, i.e., air temperature, radiant temperature, humidity, air velocity, activity, and clothing level. This metric is evaluated using the following formula:
PMV = (-8:6479 + 0:2431 C) + (0:3442 - 0:0073 C)TairWhere Tair corresponds to the air temperature and C is a constant factor that depends on the rest five factors mentioned above.
Energy saving percentage. The smart room has been equipped with two types of power meters in order to monitor energy consumption for the entire smart room as well as per electrical device inside the room. One C11 ABB power meter has been installed on the main line that powers the entire room while four Efergy ecotouch power meters monitor lights, the air-conditioning unit, the ventilation and four computer monitors. The ABB meter is able of monitoring the active power, the voltage, the current and the power factor with a total accuracy of 1% in terms of actual power consumption. Measurements are obtained in the form of electrical pulse (where each pulse denotes a 10Wh consumption) through a Solid State Relay switch. Data are propagated to the server via a TelosB mote, using the installed IPv6 network. The ecotouch power meters by Efergy are of less accuracy as they only measure apparent power, not including reactive power. Their basic use is to provide an estimation of the energy consumption and to inform the user on his energy profile rather than acting as a precise measuring tool. However, in conjunction with the ABB power we are able to obtain measurements for each device with an error in the range of 1% to 10%.
For a period of four weeks we monitored the energy consumption of the room. Then, based on the results, we came up with sophisticated scenarios that combine sensor measurements (temperature, air humidity, air quality), automations (air-conditioning, ventilation, lights, curtains) and sophisticated algorithms (in-door localization algorithms, user identification mechanisms) towards better comfort/energy trade-offs.
The UNIGE test-bed. The testbed comprised of 20 TelosB motes is a fixed network running IPv6/6LoWPAN and COAP protocols. Some motes are used as mobile motes for measuring temperature and humidity in different places of our testbed. Specified scenarios defined in the WP1 have been implemented in the testbed such as: Local adaptation to presence, energy management (partially), electric device monitoring (partially), maintenance control (partially), user centric environment customization and mobile phone ID. The topology of the network is shown in the picture below. With a star symbol is represented a mote which acts as a sensor and with a cross a mote which acts as an actuator connected to an electronic device.
Furthermore, we have added to the testbed two libelium waspmotes with NFC chips, two wasmotes with WiFi antennas and two waspmotes with Bluetooth antennas, together with their expansion boards. Moreover electrical components such as relays, cables, motors, locks have been installed to the testbed, in order to be able to control and monitor electronic devices such as lamps, curtains, fans, heaters etc. The tesbed can be accessed through the internet and a website dedicated for it and also through an android application. Each node can be accessed both separately through their unique IPv6 address and as a group of sensors with the help of a COAP server which is running in the backbone of the system.
The CTI Demo Room at Patras. As part of the CTI test-bed, a demo smart/green room is developed at the PROKAT building of the CS Department at the University of Patras. In our demo-room we will demonstrate selected green/smart building scenarios. To be more specific, by using the data sensed the sensors will control (via actuators) the various devices (lights, air-condition, heater, appliances, etc.) in order to improve the energy efficiency in the building and improve the comfort levels of the users, e.g. turn off the light/air-conditioning when people walk out of the room, open the curtains when there is enough sun light outdoors etc. For that reason, we will use actuators able to be controlled by wires or wirelessly such as: heater electro-valve, air-condition controller, blinds controller, window controller, switch for electrical appliances and light controller (dimmer).
For the purposes of developing a demo room, we have installed the electromechanical infrastructure that is necessary for enabling the control of the indoor (lights and dimmer) and the outdoor light level (motor, curtains/blinds). Furthermore, we have implemented a control panel which is the hardware interface between the wireless sensor network and the electromechanical infrastructure of the demo room and enables the wireless network to control the demo room.
This demo room will be (partially) open to FIRE users who will be able to connect to it via a web interface and test it.
CTI SenseWall test-bed at Patras. SenseWall is an experimental sensor network test-bed we have created for the implementation and engineering of distributed sensor network algorithms. It consists of 28 TelosB motes connected to a control Base Station PC via a USB tree formed by USB cables and USB hubs. It allows us to control the network and collect experimental measurements from the motes without interfering with the wireless communications, thus leaving the wireless medium free for the routing algorithms. The motes are deployed in a sector-shaped topology in order to approach the bottle-neck effect of the sensors lying close to the sink. The SenseWall testbed also includes a desktop PC that runs the MySQL server and the MoteProgrammer Java application, that allows us to massively program and control the motes. We have already implemented and experimentally evaluated several routing algorithms on SenseWall.
UNIGE IRIDA test-bed. A new testebed has been established in the UniGe. It is a testbed comprised of 49 Libelium Waspmotes. The Waspmotes have an ATmega1281 microcontroller, running at 8MHz, 8KB SRAM, 4KB EEPROM, 128KB FLASH and are equipped with a 2GB SD Card each. The SD Card can be used to store extra programs for the firmware to run, which can be uploaded, updated, executed and deleted using an Over The Air protocol (OTAP) as well. Each Waspmote is connected with a USB cable which is used mainly to provide the power necessary for operation, but it could, theoretically be used to control the Waspmote as well. The current configuration forms a 49 Waspmote 7 x 7 grid. All the Waspmotes are vertically attached to a wooden construction which leans on the wall (see picture below).
The SPECKSIM simulator. The diagram highlights the hybrid simulation capabilities by presenting the flow of communication from real-‐world devices to SpeckSim and then further to the external 3D Visualisation provided by Unity.
A 3D visualisation of the floor plan of the Informatics Forum building of the University of Edinburgh was created for a demonstrator application. It was created using both ready-made materials such as desks, computers, chairs, doors and windows with blinds, and modelled objects such as planes, cubes for the walls and lights. The camera for the scene is placed above the floor plan to offer a birds-eye view.
Sensors are placed in every room by utilizing cubes with lights shining on them. When the sensors are dormant they are red and when they receive packets at the CoAP layer, the colour turns to green. The hybrid capabilities of the simulator along with the external 3D visualisation were validated using a remote CoAP-enabled node. The node is located in an office in Geneva and captures and transmits the temperature of the room. The floor plan of the room was used to create a new game scene within the visualisation platform, Unity, in order to display accurately the environment in which the node is currently placed.