It internally deploys an AI-inspired Energy-Planner (EP) algorithm that exploits domain-specific operators to balance the trade-off between convenience and energy consumption in satisfying the Rule Automation Workflows (RAW) pipelines of users.
IoT Meta-Control Firewall has been developed by researchers and students at the Data Management Systems Laboratory (DMSL), Department of Computer Science at the University of Cyprus.
URL: https://imcf.cs.ucy.ac.cy/
Contact: imcf@cs.ucy.ac.cy
The IoT Meta-Control Firewall (IMCF) is an innovative system architecture and application, which internally deploys an AI-inspired Energy-Planner algorithm that exploits domain-specific operators to balance the trade-off between convenience/comfort and energy consumption while managing RAW pipelines of users. IMCF filters the RAW pipelines in a way that these do not collide with the long-term objectives of users (like a network firewall).
In case you have any publications resulting from the IMCF platform, please cite the following paper(s):
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"Green Planning of IoT Home Automation Workflows in Smart Buildings", Soteris Constantinou, Andreas Konstantinides, Panos K. Chrysanthis and Demetrios Zeinalipour-Yazti, ACM Transactions on Internet of Things (TIOT'22), ACM, Vol. 3, Iss. 4, pp. 1--30, New York, NY, USA, DOI: 10.1145/3549549, 2022. Download: https://www.cs.ucy.ac.cy/~dzeina/papers/tiot22-gp.pdf
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"The IoT Meta-Control Firewall", Soteris Constantinou, Andreas Konstantinidis, Demetrios Zeinalipour-Yazti, Panos K. Chrysanthis, 37th IEEE International Conference on Data Engineering (ICDE '21), IEEE Computer Society, ISBN:, pp. 12 pages, April 19 - April 22, 2021, Chania, Crete, 2021. Download: https://www.cs.ucy.ac.cy/~dzeina/papers/icde21-imcf.pdf
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"IMCF: The IoT Meta-Control Firewall for Smart Buildings", Soteris Constantinou, Antonis Vasileiou, Andreas Konstantinidis, Panos K. Chrysanthis, Demetrios Zeinalipour-Yazti, 24th International Conference on Extending Database Technology (EDBT '21), OpenProceedings.org, pp. 658--661, March 23 - March 26, 2021, Nicosia, Cyprus, 2021. Download: https://www.cs.ucy.ac.cy/~dzeina/papers/edbt21-imcf-demo.pdf
We hope that you find our IMCF useful for your research and innovation activities. We would like to have your feedback, comments and remarks and of course any experiences and test results from your own experimental setups. Questions and feedback may be sent to imcf@cs.ucy.ac.cy
Enjoy IMCF!
The IMCF Team
Copyright (c) 2021, Data Management Systems Lab (DMSL), Department of Computer Science University of Cyprus.
All rights reserved.
This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see https://www.gnu.org/licenses/gpl-3.0.html.
The software is provided “as is”, without warranty of any kind, express or implied, including but not limited to the warranties of merchantability, fitness for a particular purpose and noninfringement. in no event shall the authors or copyright holders be liable for any claim, damages or other liability, whether in an action of contract, tort or otherwise, arising from, out of or in connection with the software or the use or other dealings in the software.
Short description of the contents included in this release.
The Source code for the IMCF Java library. Lead Developer: Soteris Constantinou.
The Source code for the IMCF Laravel PHP web framework following the model–view–controller architectural pattern. Lead Developer: Soteris Constantinou.
- Anonymized measurements from a real residential apartment that comprises of a variety of sensors, submeters and readings. These are real datasets of residential data collected by the “Center for Advanced Studies in Adaptive Systems” (CASAS) at Washington State University (http://casas.wsu.edu/datasets/). CASAS serves to meet research needs around testing of the technologies using real data through the use of a smart homes environment located on the WSU Pullman campus.
- The real weather forecast dataset was acquired using Weather API on the OpenWeatherMap website and contains ∼ 5 years (2012-2017) of high temporal resolution data based on hourly measurements of various weather attributes, such as temperature, humidity, air pressure, weather description, wind direction and speed (https://openweathermap.org/api).
Project Leader: Demetris Zeinalipour