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IoT Based System for Greenhouses Remote Monitoring and Climate Control

IoT Based System for Greenhouses Remote Monitoring and Clima...

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Sciences and Techniques of Automatic Control and Computer Engineering MI-STA, IEEE international Maghreb Meeting of the conference on

作者： Yamna Ghoul Naoufel Zitouni Mohamed Ben Amor LR11ES20 Analysis Conception and Control of Systems Laboratory University of Tunis El Manar National Engineering School of Tunis Tunis Tunisia Faculty of Sciences of Tunis Loboratory of Applications of Energy Efficiency and Renewable Energies URLAPER Tunis El Manar University Tunis Tunisia Laboratory of Electronics and Information Technologies Sfax University Engineering National School Electrical Engineering Sfax Tunisia

ISBN: (数字)9798350372632

ISBN: (纸本)9798350372649

the proposed system incorporates a network of sensors strategically placed within the greenhouse to collect crucial environmental data, including temperature, humidity and soil moisture. these sensors form a connected ecosystem that continuously transmits data to a cloud-based platform. the cloud infrastructure, implemented using IBM Watson IoT platform, serves as a centralized hub for data storage, analysis, and decision-making. Furthermore, the system includes actuators responsible for controlling environmental parameters within the greenhouse. Automated climate control mechanisms are orchestrated based on real-time data insights. the implementation utilizes Raspberry Pi as the central processing unit, running Python scripts to interact with the sensors and actuators. To facilitate user-friendly interaction and real-time monitoring, the system integrates web interfaces developed using Node-Red. these interfaces provide remote access to greenhouse conditions and enable users to make informed decisions for optimal plant growth. An automated greenhouse prototype is finally implemented for monitoring and climate control system.

关键词： Temperature sensors Cloud computing Green products Prototypes Production Humidity real-time systems

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Kairos: a self-configuring approach for short and accurate event timeouts in IoT 20

Kairos: a self-configuring approach for short and accurate e...

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17th EAI international conference on Mobile and Ubiquitous systems - computing, Networking and Services (MobiQuitous)

作者： Peros, Stefanos Aras, Emekcan Joosen, Wouter Hughes, Danny Katholieke Univ Leuven Imec DistriNet Leuven Belgium

ISBN: (纸本)9781450388405

the Internet of things (IoT) consists of embedded sensors that transmit events over a wireless network. Complex event processing provides powerful abstractions to aggregate and analyze relationships among event streams in real time, which can improve IoT application development and management. A key challenge are stream imperfections, because of the non-deterministic nature of IoT: events can be delayed due to variance in delay, or may even be missing due to packet loss. timeouts are used to handle stream imperfections, distinguishing between delayed and lost events. For some applications, missing delayed events is costly, as the quality of the result depends on the presence of all inputs, but reacting too late to event non-arrivals can also lead to incorrect results. State-of-the-art results in timeouts that are impractically large when little to no missed events are tolerated by the application. We propose Kairos, a novel, self-configuring technique for determining event arrival timeouts in IoT that are both small and ensure that little to no events are missed, while also eliminating the overhead and complexity of user configuration. We evaluate our approach against the state-of-the-art using two representative IoT networks: SmartMesh IP and LoRaWAN. the results show that our solution is capable of reducing timeouts by up to two orders of magnitude even when little to no missed events are tolerated, thus satisfying the aforementioned application requirements.

关键词： internet of things cyber-physical systems timeliness timeout time management late events

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the Evolution of Non-invasive Hemoglobin Measurement with IoT and AI-Based Optical Sensors

The Evolution of Non-invasive Hemoglobin Measurement with Io...

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international conference on Electrical Engineering, Computer Science and Informatics (EECSI)

作者： Tole Sutikno Lina Handayani Rochana Ruliyandari Oktomi Wijaya Hendril Satrian P Watra Arsadiando Master Program of Electrical Engineering Universitas Ahmad Dahlan Yogyakarta Indonesia Faculty of Public Health Universitas Ahmad Dahlan Yogyakarta Indonesia Embedded System and Power Electronics Research Group (ESPERG) Yogyakarta Indonesia

ISBN: (数字)9798350355314

ISBN: (纸本)9798350355321

Hemoglobin measurement has significantly evolved with the integration of IoT and artificial intelligence (AI) technologies. this paper presents the evolution of non-invasive hemoglobin measurement using IoT and AI-based optical sensors. IoT and AI-based optical sensors have revolutionized the field of hemoglobin quantification, allowing us to measure this important biomarker in a way that isn't invasive or difficult to handle. the use of optical sensing technology, along with IoT frameworks and AI methods, has improved the accuracy and usefulness of hemoglobin tests, showing a promising way to improve healthcare outcomes. However, challenges remain in the field of non-invasive hemoglobin measurement, such as precision constraints, data security, and privacy safeguards. Despite these challenges, the future landscape of non-invasive hemoglobin measurement leveraging IoT and AI-powered optical sensors appears poised to transform healthcare delivery significantly. Together, IoT and AI-based optical sensors have the potential to revolutionize healthcare monitoring and diagnosis.

关键词： Accuracy Electric variables measurement Medical services Optical variables measurement real-time systems Optical sensors Reliability Artificial intelligence Medical diagnostic imaging Monitoring

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Deterministic OpenMP and the LBP Parallelizing Manycore Processor 16th

Deterministic OpenMP and the LBP Parallelizing Manycore Proc...

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16th international conference on Parallel computing Technologies, PaCT 2021

作者： Goossens, Bernard Louetsi, Kenelm Parello, David LIRMM Univ Montpellier Montpellier France DALI Univ Perpignan Perpignan France

ISBN: (纸本)9783030863586

Multicore processors are becoming standard called as COTS (Commercial Off the Shelf) processors but can not be fully used in the context of critical real time systems. OpenMP is one of the most used programming models to build parallel programs able to exploit such multicore processors. A lot of work try to tackle the issue of the determinism of parallel programming models. the critical real time system face an unpredictability wall of parallel programs. this paper presents Deterministic OpenMP, a new runtime for OpenMP programs, and the Little Big Processor (LBP) manycore processor design. their aim is to help to solve the non determinism problem at the programming level but also at the execution level. When run on LBP, a Deterministic OpenMP code produces cycle by cycle deterministic computations. LBP and Deterministic OpenMP are particularly suited to safely accelerate real time embedded applications through their parallel execution. © 2021, Springer Nature Switzerland AG.

关键词： real time systems

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Interrupting real-time IoT Tasks: How Bad Can It Be to Connect Your Critical embedded System to the Internet? 39

Interrupting Real-Time IoT Tasks: How Bad Can It Be to Conne...

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39th IEEE international Performance computing and Communications conference (IPCCC)

作者： Behnke, Ilja Pirl, Lukas thamsen, Lauritz Danicki, Robert Polze, Andreas Kao, Odej Tech Univ Berlin Berlin Germany Hasso Plattner Inst Potsdam Germany

ISBN: (纸本)9781728198293

embedded systems have been used to control physical environments for decades. Usually, such use cases require low latencies between commands and actions as well as a high predictability of the expected worst-case delay. To achieve this on small, low-powered microcontrollers, real-time Operating systems (RTOSs) are used to manage the different tasks on these machines as deterministically as possible. However, with the advent of the Internet of things (IoT) in industrial applications, the same embedded systems are now equipped with networking capabilities, possibly endangering critical real-time systems through an open gate to interrupts. this paper presents our initial study of the impact network connections can have on real-time embedded systems. Specifically, we look at three aspects: the impact of network-generated interrupts, the overhead of the related networking tasks, and the feasibility of sharing computing resources between networking and real-time tasks. We conducted experiments on two setups: One treating NICs and drivers as black boxes and one simulating network interrupts on the machines. the preliminary results show that a critical task performance loss of up to 6.67% per received packet per second could be induced where lateness impacts of 1% per packet per second can be attributed exclusively to ISR-generated delays.

关键词： Internet of things real-time Interrupts Cyber Physical systems embedded systems

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embedded System Learning Platform for Developing Economies 23rd

Embedded System Learning Platform for Developing Economies

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23rd international conference on Interactive Collaborative Learning (ICL) / 49th IGIP international conference on Engineering Pedagogy - Educating Engineers for Future Industrial Revolutions

作者： Chamunorwa, Tinashe Ursutiu, D. Samoila, C. Modran, Horia Alexandru Transilvania Univ Brasov Brasov Romania Romanian Acad Scientists Bucharest Romania Romanian Acad Tech Sci Brasov Romania

ISBN: (纸本)9783030682019;9783030682002

the continual research of electronic embedded system platforms for teaching and learning is of paramount importance. this is to increase the impact on a universities' ability to lead in technological advancement with goals to enhance innovation and accelerate the concept-to-deployment process. Technological progress in the fields of electronics, wireless communication, cognitive computing, and robotics has caused almost everything which connects to electricity to have a small processor and sensor embedded with itself [1]. Cognitive or Intelligent embedded systems are the 'core' of trends such as: reduced energy consumption, deep learning applications, improved security for embedded devices, cloud connectivity and mesh networking, and visualization tools with real time data. this paper is aimed at stimulating design and innovation in electronics education through the rapid prototyping of configurable embedded systems. It also covers remote access functionality is also shown using cloud services. Divided into two parts, this paper gives design examples for both an elevator controller and a Data Acquisition (DAQ) system design. Focus was on the Programmable System on Chip (PSoC) 6 based kit, PSoC Creator software, and Laboratory Virtual Instrumentation Engineering Workbench (LabVIEW) as rapid prototyping and learning platforms for digital and analog system designs. the Universal Digital Block (UDB) editor in PSoC Creator software was used to configure PSoC chip digital blocks and design a Finite State Machine (FSM) based elevator controller, which acquired digital signals and gave corresponding output. LabVIEW was used as a signal analysis tool and was also used to send results for online access and display. the PSoC and LabVIEW ecosystems are utilized here to bring an innovative paradigm into the embedded system design. these two platforms, especially combined with the virtual instrumentation concept, offer configurability and monetary value. this paper shows that the

关键词： AFE FPGA FSM LabVIEW PSOC UDB Verilog

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Cloud computing's IoT based thingSpeak, NodeMCU for Weather Monitoring

Cloud Computing's IoT based ThingSpeak, NodeMCU for Weather ...

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Electronics and Sustainable Communication systems (ICESC), 2020 international conference on

作者： Suresh Chinnathampy M Jobin C J Jarin T V.P.M.B. Aarthi N Raghavendran Department of Electronics and Communication Engineering Vel Tech High Tech Dr. Rangarajan Dr. Sakunthala Engineering College Chennai Department of Mechanical Engineering Jyothi Engineering College Thrissur Kerala India Department of EEE Jyothi Engineering College Thrissur Kerala India Department of ECE School of Electronics Electrical and Biomedical Technology Kalasalingam Academy of Research and Education Krishnankoil Srivilliputtur Department of Artificial intelligence and Date Science Engineering R.M.K. College of Engineering and Technology (An Autonomous Institution) Chennai

ISBN: (数字)9798350379945

ISBN: (纸本)9798350379952

In this research work, a cloud-based Internet of things (IoT) system for weather monitoring in real-time is presented by integrating the thingSpeak platform, the ESP32 microcontroller, and several sensors, such as rain, soil moisture, and temperature sensors (DHT11). the ESP32 acts as the central hub, integrating sensors and wireless connectivity for data acquisition and transmission. Data collected is securely stored, visualized, and analyzed on thingSpeak, enabling remote monitoring and decision-making. the system's modular design allows easy expansion and customization, accommodating additional sensors or functionalities. Leveraging cloud computing, this IoT solution offers scalability, accessibility, and data sharing for applications like agriculture and environmental monitoring. With efficient data processing and transmission, even in resource-constrained environments, and collaboration features through thingSpeak, this research contributes to advancing cloud-based IoT systems for weather monitoring.

关键词： Temperature sensors Wireless communication Cloud computing Wireless sensor networks Scalability Soil moisture Sensor systems Sensors Internet of things Meteorology

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A CNN-based Audio Sensor for Rainfall Estimation: Implementation on embedded Board

A CNN-based Audio Sensor for Rainfall Estimation: Implementa...

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IEEE international Workshop on Intelligent Data Acquisition and Advanced computing systems: Technology and applications

作者： Michele Russo Valerio Francesco Puglisi Roberta Avanzato Francesco Beritelli VICOSYSTEMS S.R.L. Viale Odorico da Pordenone Catania Italy DMI - University of Catania Catania Italy DIEEI - University of Catania Catania Italy

ISBN: (纸本)9781665426060

At present, one of the main issues of interest is climate change. It triggers calamitous phenomena (fires, hydrogeological instability and many others) that put crops, vegetation and even human beings at risk. Considering the phenomenon of hydrogeological instability, there is a wide range of smart application contexts (for example, smart city, smart road and smart agriculture), which require a real-time rainfall level monitoring, recognition and classification system. this system is supposed to provide accurate and real-time estimates of rain intensity and alert those in charge in order to reduce the risks associated with the various application contexts. thus, the present paper proposes an audio sensor enabled real-time audio rainfall classification, based on 1-D convolutional neural network (CNN) which offers 95% classification accuracy in five rainfall intensity classes.

关键词： Rain Smart cities Roads Estimation Vegetation mapping real-time systems Sensor systems

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Development of Mobile Application for Skin Cancer Detection Using Deep Learning Models

Development of Mobile Application for Skin Cancer Detection ...

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international conference on Soft computing and Machine Intelligence (ISCMI)

作者： Ranpreet Kaur Hamid GholamHosseini Paula Iskander Radwa Taha Shereen Afifi Software Engineering & AI Media Design School Auckland New Zealand School of Engineering Auckland University of Technology Auckland New Zealand Media Engineering and Technology German University in Cario Cairo Egypt

ISBN: (数字)9798331518127

ISBN: (纸本)9798331518134

Skin cancer remains the leading cause of cancer-related mortality worldwide, emphasizing the critical need for accurate and timely diagnosis. the current clinical treatments are time-consuming and susceptible to human error, which can delay treatment and affect patient outcomes. this research addresses these challenges by making two major contributions to the field. Firstly, four fine-tuned deep neural models; MobileNetV2, MobileNetV3, EfficientNetV2, and ResNet50; were evaluated across three distinct experimental settings to explore their potential in accurately classifying skin lesions. Among the models tested, MobileNetV3 outperformed the others, achieving the highest accuracy of 80.17% in categorizing four types of skin cancer in dermoscopic images and 79.17% in clinical images. Secondly, the study indicated that the development of an accessible mobile application capable of detecting skin cancer at its early stages is crucial. this app leverages the MobileNetV3 model to provide a quick and reliable tool for early diagnosis, thereby broadening access to life-saving interventions and reducing the burden of treatments on healthcare systems.

关键词： Accuracy Mortality Medical services Skin Mobile applications Reliability Lesions Machine intelligence Skin cancer Residual neural networks

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Robust Motion Control for Aerial Robotic systems in Monitoring applications

Robust Motion Control for Aerial Robotic Systems in Monitori...

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IEEE international conference on Smart Energy Grid Engineering (SEGE)

作者： Hugo Yañez-Badillo Francisco Beltran-Carbajal Irvin Lopez-Garcia Daniel Galvan-Perez Alejandro Alvarez-Diaz Jose Luis Hernandez-Avila Ivan Rivas-Cambero Departamento de Investigación TecNM: Tecnológico de Estudios Superiores de Tianguistenco Tianguistenco Estado de México Mexico Departamento de Energía Universidad Autónoma Metropolitana Unidad Azcapotzalco Mexico City Mexico Departamento de Posgrado Universidad Politécnica de Tulancingo Tulancingo de Bravo Hidalgo Mexico División de Ingeniería Mecatrónica TecNM: Tecnológico de Estudios Superiores de Tianguistenco Tianguistenco Estado de México Mexico

Mobile robots usage have allowed a properly performance of complex tasks in various fields without human intervention. Unmanned aerial robots have been successfully used in monitoring applications within indoor and outdoor scenarios. the main contribution of this research is to introduce a novel robust neural sliding-mode control for a four-rotor aerial robot in monitoring tasks. To verify the effectiveness of the proposed motion control scheme, it is considered a simulation scenario where the vehicle is subjected to unknown disturbances while the robot is flying towards different operation points, as required in real-time monitoring applications. Bézier polynomials are suitably integrated in the motion control scheme to smooth the system motion. Additional case study is also included where B-spline artificial neural networks are efficiently introduced for improving the system performance while maintaining its stability despite random undesired abrupt position changes due to the induced forces by wind. Finally, to highlight the effectiveness of the introduced controller, the vehicle is simulated in a virtual scenario where a rapidly exploring random tree (RRT) algorithm is implemented for determining the best path in a constrained space. this preliminary results effectively promote the development of cyber-physical systems for monitoring application management, as required in the electric power systems.

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