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Machine Learning brings intelligence services to IoT systems, with Edge Computing contributing for edge nodes to be part of these services, allowing data to be processed directly in the nodes in real time. This paper introduces a new way of creating a self-configurable IoT node, in terms of communications, supported by machine learning and edge computing, in order to achieve a better efficiency in terms of power consumption, as well as a comparison between regression models and between deploying them in edge or cloud fashions, with a real case implementation. The correct choice of protocol and configuration parameters can make the difference between a device battery lasting 100 times more. The proposed method predicts the energy consumption and quality of signal using regressions based on node location, distance and obstacles and the transmission power used. With an accuracy of 99.88% and a margin of error of 1.504 mA for energy consumption and 98.68% and a margin of error of 1.9558 dBm for link quality, allowing the node to use the best transmission power values for reliability and energy efficiency. With this it is possible to achieve a network that can reduce up to 68% the energy consumption of nodes while only compromising in 7% the quality of the network. Besides that, edge computing proves to be a better solution when energy efficient nodes are needed, as less messages are exchanged, and the reduced latency allows nodes to be configured in less time.
Andre F. X. Gloria; Pedro J. A. Sebastiao. Autonomous Configuration of Communication Systems for IoT Smart Nodes Supported by Machine Learning. IEEE Access 2021, 9, 75021 -75034.
AMA StyleAndre F. X. Gloria, Pedro J. A. Sebastiao. Autonomous Configuration of Communication Systems for IoT Smart Nodes Supported by Machine Learning. IEEE Access. 2021; 9 ():75021-75034.
Chicago/Turabian StyleAndre F. X. Gloria; Pedro J. A. Sebastiao. 2021. "Autonomous Configuration of Communication Systems for IoT Smart Nodes Supported by Machine Learning." IEEE Access 9, no. : 75021-75034.
Presently, saving natural resources is increasingly a concern, and water scarcity is a fact that has been occurring in more areas of the globe. One of the main strategies used to counter this trend is the use of new technologies. On this topic, the Internet of Things has been highlighted, with these solutions being characterized by offering robustness and simplicity, while being low cost. This paper presents the study and development of an automatic irrigation control system for agricultural fields. The developed solution had a wireless sensors and actuators network, a mobile application that offers the user the capability of consulting not only the data collected in real time but also their history and also act in accordance with the data it analyses. To adapt the water management, Machine Learning algorithms were studied to predict the best time of day for water administration. Of the studied algorithms (Decision Trees, Random Forest, Neural Networks, and Support Vectors Machines) the one that obtained the best results was Random Forest, presenting an accuracy of 84.6%. Besides the ML solution, a method was also developed to calculate the amount of water needed to manage the fields under analysis. Through the implementation of the system it was possible to realize that the developed solution is effective and can achieve up to 60% of water savings.
André Glória; João Cardoso; Pedro Sebastião. Sustainable Irrigation System for Farming Supported by Machine Learning and Real-Time Sensor Data. Sensors 2021, 21, 3079 .
AMA StyleAndré Glória, João Cardoso, Pedro Sebastião. Sustainable Irrigation System for Farming Supported by Machine Learning and Real-Time Sensor Data. Sensors. 2021; 21 (9):3079.
Chicago/Turabian StyleAndré Glória; João Cardoso; Pedro Sebastião. 2021. "Sustainable Irrigation System for Farming Supported by Machine Learning and Real-Time Sensor Data." Sensors 21, no. 9: 3079.
Water is a crucial natural resource, and it is widely mishandled, with an estimated one third of world water utilities having loss of water of around 40% due to leakage. This paper presents a proposal for a system based on a wireless sensor network designed to monitor water distribution systems, such as irrigation systems, which, with the help of an autonomous learning algorithm, allows for precise location of water leaks. The complete system architecture is detailed, including hardware, communication, and data analysis. A study to discover the best machine learning algorithm between random forest, decision trees, neural networks, and Support Vector Machine (SVM) to fit leak detection is presented, including the methodology, training, and validation as well as the obtained results. Finally, the developed system is validated in a real-case implementation that shows that it is able to detect leaks with a 75% accuracy.
João Alves Coelho; André Glória; Pedro Sebastião. Precise Water Leak Detection Using Machine Learning and Real-Time Sensor Data. IoT 2020, 1, 474 -493.
AMA StyleJoão Alves Coelho, André Glória, Pedro Sebastião. Precise Water Leak Detection Using Machine Learning and Real-Time Sensor Data. IoT. 2020; 1 (2):474-493.
Chicago/Turabian StyleJoão Alves Coelho; André Glória; Pedro Sebastião. 2020. "Precise Water Leak Detection Using Machine Learning and Real-Time Sensor Data." IoT 1, no. 2: 474-493.
With the quick advance of technology and the appearance of low cost/high performance solutions, it became possible to develop new solutions in order to achieve sustainability. This paper proposes a scheme for monitor and control farming irrigation in order to measure and administrate the right amount of water needed to avoid overirrigation, preventing and alerting to risk situations, that require immediate intervention. This paper provides a methodology for an IoT system with a wireless sensor network installed on the ground and a main server, running machine learning algorithms, to process the collected data. Communications will be conducted using NB-IoT and LoRa. In order to give the owner the capability of consult the collected data and control his property, an iOS application completes the methodology, allowing the system to be remote and to be used anywhere, only requiring an internet connection.
Joao Cardoso; André Glória; Pedro Sebastiao. A Methodology for Sustainable Farming Irrigation using WSN, NB-IoT and Machine Learning. 2020 5th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM) 2020, 1 -6.
AMA StyleJoao Cardoso, André Glória, Pedro Sebastiao. A Methodology for Sustainable Farming Irrigation using WSN, NB-IoT and Machine Learning. 2020 5th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM). 2020; ():1-6.
Chicago/Turabian StyleJoao Cardoso; André Glória; Pedro Sebastiao. 2020. "A Methodology for Sustainable Farming Irrigation using WSN, NB-IoT and Machine Learning." 2020 5th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM) , no. : 1-6.
This paper introduces a new methodology to predict power usage in irrigation system, using smartgrid data and Random Forest, in order to improve energy efficiency of these systems. The proposed methodology is able to predict energy consumption of a given timestamp based on previous information, using Random Forest Regressions. Then using a Random Forest Classifier, is able to classify that timestamp in either an ideal or not period to irrigate, based on network capacity and energy price, with the main goal of reducing the costs of energy to the client. Besides the methodology, this paper includes its implementation and experimental results. It was possible to achieve a 0.0468 Wh error in the prediction and a 87% accuracy in the classification.
André Glória; Joao Cardoso; Pedro Sebasliao. Improve Energy Efficiency of Irrigation Systems using Smartgrid and Random Forest. 2020 5th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM) 2020, 1 -6.
AMA StyleAndré Glória, Joao Cardoso, Pedro Sebasliao. Improve Energy Efficiency of Irrigation Systems using Smartgrid and Random Forest. 2020 5th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM). 2020; ():1-6.
Chicago/Turabian StyleAndré Glória; Joao Cardoso; Pedro Sebasliao. 2020. "Improve Energy Efficiency of Irrigation Systems using Smartgrid and Random Forest." 2020 5th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM) , no. : 1-6.
This paper introduces a new way of managing water in irrigation systems, which can be applied to gardens or agricultural fields, replacing human intervention with Wireless Sensor Networks. A typical irrigation system wastes on average 30% of the water used, due to poor management and configuration. This sustainable irrigation system allows a better efficiency in the process of irrigation that can lead to savings for the end user, not only monetary but also in natural resources, such as water and energy, leading to a more sustainable environment. The system can retrieve real time data and use them to determinate the correct amount of water to be used in a garden. With this solution, it is possible to save up to 34% of water when using sensor data from temperature, humidity and soil moisture, or up to 26% when using only temperature inputs. Besides a detailed system architecture, this paper includes a real case scenario implementation and results discussion.
André Glória; Carolina Dionisio; Gonçalo Simões; João Cardoso; Pedro Sebastião. Water Management for Sustainable Irrigation Systems Using Internet-of-Things†. Sensors 2020, 20, 1402 .
AMA StyleAndré Glória, Carolina Dionisio, Gonçalo Simões, João Cardoso, Pedro Sebastião. Water Management for Sustainable Irrigation Systems Using Internet-of-Things†. Sensors. 2020; 20 (5):1402.
Chicago/Turabian StyleAndré Glória; Carolina Dionisio; Gonçalo Simões; João Cardoso; Pedro Sebastião. 2020. "Water Management for Sustainable Irrigation Systems Using Internet-of-Things†." Sensors 20, no. 5: 1402.
This paper introduces a new way of creating a self-configurable LoRa end device in order to achieve a better efficiency in terms of power consumption. The correct configuration of LoRa parameters can make the difference between a device battery last 100 times more. The proposed method evaluates the sensibility of the receiver when the transmitter uses an array of different Transmission Powers to decide which is the best to create a viable link. Besides the proposed methodology, this paper includes a real case scenario implementation and result discussions.
André Glória; Carolina Dionisio; Goncalo Simoes; Pedro Sebastiao. LoRa Transmission Power Self Con?guration for Low Power End Devices. 2019 22nd International Symposium on Wireless Personal Multimedia Communications (WPMC) 2019, 1 -6.
AMA StyleAndré Glória, Carolina Dionisio, Goncalo Simoes, Pedro Sebastiao. LoRa Transmission Power Self Con?guration for Low Power End Devices. 2019 22nd International Symposium on Wireless Personal Multimedia Communications (WPMC). 2019; ():1-6.
Chicago/Turabian StyleAndré Glória; Carolina Dionisio; Goncalo Simoes; Pedro Sebastiao. 2019. "LoRa Transmission Power Self Con?guration for Low Power End Devices." 2019 22nd International Symposium on Wireless Personal Multimedia Communications (WPMC) , no. : 1-6.
This paper introduces a new way to analyze temperature distribution from an air conditioning unit inside an office using Wireless Sensor Networks and Machine Learning algorithms. The system is able to retrieve real time temperature data and use it to analyze if the air conditioning unit is influencing the temperature inside an office using the temperature difference from various points inside the office. Besides the system architecture, this paper includes a real case scenario implementation and a comparison and discussion of the result for the multiple Machine Learning algorithms applied to categorize if the air conditioner is affecting the office temperature.
André Glória; Pedro Sebastiao. Temperature Distribution Analyses with Wireless Sensor Networks and Machine Learning. 2019 International Conference on Sensing and Instrumentation in IoT Era (ISSI) 2019, 1 -6.
AMA StyleAndré Glória, Pedro Sebastiao. Temperature Distribution Analyses with Wireless Sensor Networks and Machine Learning. 2019 International Conference on Sensing and Instrumentation in IoT Era (ISSI). 2019; ():1-6.
Chicago/Turabian StyleAndré Glória; Pedro Sebastiao. 2019. "Temperature Distribution Analyses with Wireless Sensor Networks and Machine Learning." 2019 International Conference on Sensing and Instrumentation in IoT Era (ISSI) , no. : 1-6.
This paper proposes a new scheme for monitoring and controlling the swimming pool's quality through a low-cost system based on wireless sensor networks, which can reduce the requirements for human intervention in the swimming pool maintenance. The main purpose of this system is to provide resources savings for the final user in financial and natural resources, contributing to a sustainable environment. This article also presents a mobile application for interacting with the proposed system which enables users with administrator permissions to control some actions in the swimming pool, in order to stabilize some required parameters for its good quality.
Goncalo Simoes; Carolina Dionisio; André Glória; Pedro Sebastiao; Nuno Souto. Smart System for Monitoring and Control of Swimming Pools. 2019 IEEE 5th World Forum on Internet of Things (WF-IoT) 2019, 829 -832.
AMA StyleGoncalo Simoes, Carolina Dionisio, André Glória, Pedro Sebastiao, Nuno Souto. Smart System for Monitoring and Control of Swimming Pools. 2019 IEEE 5th World Forum on Internet of Things (WF-IoT). 2019; ():829-832.
Chicago/Turabian StyleGoncalo Simoes; Carolina Dionisio; André Glória; Pedro Sebastiao; Nuno Souto. 2019. "Smart System for Monitoring and Control of Swimming Pools." 2019 IEEE 5th World Forum on Internet of Things (WF-IoT) , no. : 829-832.
This paper introduces a new way of maintaining a sustainable irrigation system, applied to gardens or agricultural fields, replacing human intervention with Wireless Sensor Net-works, in order to achieve a better efficiency in the process that can lead to savings for the final user, not only monetary but also in natural resources, such as water and energy, leading to a more sustainable environment. The system can retrieve real time data and use them to determinate the correct amount of water to be used in the garden in order to keep it healthy. Besides the system architecture, this paper includes a real case scenario implementation and result discussions.
André Glória; Carolina Dionisio; Goncalo Simoes; Pedro Sebastiao; Nuno Souto. WSN Application for Sustainable Water Management in Irrigation Systems. 2019 IEEE 5th World Forum on Internet of Things (WF-IoT) 2019, 833 -836.
AMA StyleAndré Glória, Carolina Dionisio, Goncalo Simoes, Pedro Sebastiao, Nuno Souto. WSN Application for Sustainable Water Management in Irrigation Systems. 2019 IEEE 5th World Forum on Internet of Things (WF-IoT). 2019; ():833-836.
Chicago/Turabian StyleAndré Glória; Carolina Dionisio; Goncalo Simoes; Pedro Sebastiao; Nuno Souto. 2019. "WSN Application for Sustainable Water Management in Irrigation Systems." 2019 IEEE 5th World Forum on Internet of Things (WF-IoT) , no. : 833-836.
With the rapid increase of smart devices, keeping track of household consumptions is a service that starts to be automated. This paper presents a proposal for a system based on wireless sensor networks designed for the purpose of monitoring and controlling environment parameters of a smart home. In order to obtain an efficient and inexpensive system, a study was made to select the best hardware and software solutions for this system. This system allows the user, through an Android application, to view all the information collected by the sensors, and consequently act in a way to make his home more sustainable. The main advantage of this system is to take into account that all its components are small, practical and with high efficiency, in addition it allows an easy installation and in order to get involved with the inner environment, another advantage is to allow system interaction with the user.
Carolina Dionisio; Goncalo Simoes; André Glória; Pedro Sebastiao; Nuno Souto. Distributed Sensing Solution for Home Efficiency Tracking. 2019 IEEE 5th World Forum on Internet of Things (WF-IoT) 2019, 825 -828.
AMA StyleCarolina Dionisio, Goncalo Simoes, André Glória, Pedro Sebastiao, Nuno Souto. Distributed Sensing Solution for Home Efficiency Tracking. 2019 IEEE 5th World Forum on Internet of Things (WF-IoT). 2019; ():825-828.
Chicago/Turabian StyleCarolina Dionisio; Goncalo Simoes; André Glória; Pedro Sebastiao; Nuno Souto. 2019. "Distributed Sensing Solution for Home Efficiency Tracking." 2019 IEEE 5th World Forum on Internet of Things (WF-IoT) , no. : 825-828.
Andre Gloria; Francisco Cercas; Nuno Souto. Comparison of communication protocols for low cost Internet of Things devices. 2017 South Eastern European Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM) 2017, 1 .
AMA StyleAndre Gloria, Francisco Cercas, Nuno Souto. Comparison of communication protocols for low cost Internet of Things devices. 2017 South Eastern European Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM). 2017; ():1.
Chicago/Turabian StyleAndre Gloria; Francisco Cercas; Nuno Souto. 2017. "Comparison of communication protocols for low cost Internet of Things devices." 2017 South Eastern European Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM) , no. : 1.
André Glória; Francisco Cercas; Nuno Souto. Design and implementation of an IoT gateway to create smart environments. Procedia Computer Science 2017, 109, 568 -575.
AMA StyleAndré Glória, Francisco Cercas, Nuno Souto. Design and implementation of an IoT gateway to create smart environments. Procedia Computer Science. 2017; 109 ():568-575.
Chicago/Turabian StyleAndré Glória; Francisco Cercas; Nuno Souto. 2017. "Design and implementation of an IoT gateway to create smart environments." Procedia Computer Science 109, no. : 568-575.