Forecasting green roofs’ potential in improving building thermal performance and mitigating urban heat island in the Mediterranean area: An artificial intelligence-based approach

Green roofs are widely used in hot or cold climates mainly because they are capable to improve the energy efficiency of buildings and, when implemented at a large scale, reducing air pollution and the urban heat island effect (UHI) in urban contexts. Artificial Neural Network (ANN) black-box algorithms are a valid alternative to studying complex systems. However, the literature highlights - quite surprisingly – none of the available research refers to coupling ANNs and green roofs in the Mediterranean area, where green roofs are instead considered one of the most suitable technologies to reduce the high cooling demand. Therefore, the objective of this research work is to create and validate an ANN for the prediction of the monthly green roof’s internal and external surface temperatures and the monthly internal air temperature, starting from different green roof parameters and climatic variables. Specifically, the ANN was created with reference to a Mediterranean climate considering an existing green roof on a building of the University of Palermo characterized by a cooling demand predominance; 180 green roof configurations, obtained by varying the characteristic parameters of vegetation (plant height, leaf area index and leaf reflectivity) and the substrate thickness and thermophysical properties (lightweight and heavyweight), were dynamically simulated on an hourly basis to build the training dataset. In addition, other 72 green roof configurations were simulated to generate the dataset for the validation purpose of the ANN accuracy. The optimal ANN-related architecture consists of 90 neurons with one hidden layer and guarantees very high accuracy predictions. The outcomes of this research represent a useful tool to determine the thermal response of green roofs and their impact on the building energy demand and indoor thermal comfort and UHI mitigation

Advanced photonic and electronic systems WILGA 2018

WILGA annual symposium on advanced photonic and electronic systems has been organized by young scientist for young scientists since two decades. It traditionally gathers around 400 young researchers and their tutors. Ph.D students and graduates present their recent achievements during well attended oral sessions. Wilga is a very good digest of Ph.D. works carried out at technical universities in electronics and photonics, as well as information sciences throughout Poland and some neighboring countries. Publishing patronage over Wilga keep Elektronika technical journal by SEP, IJET and Proceedings of SPIE. The latter world editorial series publishes annually more than 200 papers from Wilga. Wilga 2018 was the XLII edition of this meeting. The following topical tracks were distinguished: photonics, electronics, information technologies and system research. The article is a digest of some chosen works presented during Wilga 2018 symposium. WILGA 2017 works were published in Proc. SPIE vol.10445. WILGA 2018 works were published in Proc. SPIE vol.10808

Autonomous Sensing Nodes for IoT Applications

The present doctoral thesis fits into the energy harvesting framework, presenting the development of low-power nodes compliant with the energy autonomy requirement, and sharing common technologies and architectures, but based on different energy sources and sensing mechanisms. The adopted approach is aimed at evaluating multiple aspects of the system in its entirety (i.e., the energy harvesting mechanism, the choice of the harvester, the study of the sensing process, the selection of the electronic devices for processing, acquisition and measurement, the electronic design, the microcontroller unit (MCU) programming techniques), accounting for very challenging constraints as the low amounts of harvested power (i.e., [μW, mW] range), the careful management of the available energy, the coexistence of sensing and radio transmitting features with ultra-low power requirements. Commercial sensors are mainly used to meet the cost-effectiveness and the large-scale reproducibility requirements, however also customized sensors for a specific application (soil moisture measurement), together with appropriate characterization and reading circuits, are also presented. Two different strategies have been pursued which led to the development of two types of sensor nodes, which are referred to as 'sensor tags' and 'self-sufficient sensor nodes'. The first term refers to completely passive sensor nodes without an on-board battery as storage element and which operate only in the presence of the energy source, provisioning energy from it. In this thesis, an RFID (Radio Frequency Identification) sensor tag for soil moisture monitoring powered by the impinging electromagnetic field is presented. The second term identifies sensor nodes equipped with a battery rechargeable through energy scavenging and working as a secondary reserve in case of absence of the primary energy source. In this thesis, quasi-real-time multi-purpose monitoring LoRaWAN nodes harvesting energy from thermoelectricity, diffused solar light, indoor white light, and artificial colored light are presented

개별 이온 및 작물 생육 센싱 기반의 정밀 수경재배 양액 관리 시스템

학위논문 (박사) -- 서울대학교 대학원 : 농업생명과학대학 바이오시스템·소재학부(바이오시스템공학), 2020. 8. 김학진.In current closed hydroponics, the nutrient solution monitoring and replenishment are conducted based on the electrical conductivity (EC) and pH, and the fertigation is carried out with the constant time without considering the plant status. However, the EC-based management is unable to detect the dynamic changes in the individual nutrient ion concentrations so the ion imbalance occurs during the iterative replenishment, thereby leading to the frequent discard of the nutrient solution. The constant time-based fertigation inevitably induces over- or under-supply of the nutrient solution for the growing plants. The approaches are two of the main causes of decreasing water and nutrient use efficiencies in closed hydroponics. Regarding the issues, the precision nutrient solution management that variably controls the fertigation volume and corrects the deficient nutrient ions individually would allow both improved efficiencies of fertilizer and water use and increased lifespan of the nutrient solution. The objectives of this study were to establish the precision nutrient solution management system that can automatically and variably control the fertigation volume based on the plant-growth information and supply the individual nutrient fertilizers in appropriate amounts to reach the optimal compositions as nutrient solutions for growing plants. To achieve the goal, the sensing technologies for the varying requirements of water and nutrients were investigated and validated. Firstly, an on-the-go monitoring system was constructed to monitor the lettuces grown under the closed hydroponics based on the nutrient film technique for the entire bed. The region of the lettuces was segmented by the excess green (ExG) and Otsu method to obtain the canopy cover (CC). The feasibility of the image processing for assessing the canopy (CC) was validated by comparing the computed CC values with the manually analyzed CC values. From the validation, it was confirmed the image monitoring and processing for the CC measurements were feasible for the lettuces before harvest. Then, a transpiration rate model using the modified Penman-Monteith equation was fitted based on the obtained CC, radiation, air temperature, and relative humidity to estimate the water need of the growing lettuces. Regarding the individual ion concentration measurements, two-point normalization, artificial neural network, and a hybrid signal processing consisting of the two-point normalization and artificial neural network were compared to select an effective method for the ion-selective electrodes (ISEs) application in continuous and autonomous monitoring of ions in hydroponic solutions. The hybrid signal processing showed the most accuracy in sample measurements, but the vulnerability to the sensor malfunction made the two-point normalization method with the most precision would be appropriate for the long-term monitoring of the nutrient solution. In order to determine the optimal injection amounts of the fertilizer salts and water for the given target individual ion concentrations, a decision tree-based dosing algorithm was designed. The feasibility of the dosing algorithm was validated with the stepwise and varying target focusing replenishments. From the results, the ion-specific replenishments formulated the compositions of the nutrient solution successfully according to the given target values. Finally, the proposed sensing and control techniques were integrated to implement the precision nutrient solution management, and the performance was verified by a closed lettuce cultivation test. From the application test, the fertigation volume was reduced by 57.4% and the growth of the lettuces was promoted in comparison with the constant timer-based fertigation strategy. Furthermore, the system successfully maintained the nutrient balance in the recycled solution during the cultivation with the coefficients of variance of 4.9%, 1.4%, 3.2%, 5.2%, and 14.9%, which were generally less than the EC-based replenishment with the CVs of 6.9%, 4.9%, 23.7%, 8.6%, and 8.3% for the NO3, K, Ca, Mg, and P concentrations, respectively. These results implied the developed precision nutrient solution management system could provide more efficient supply and management of water and nutrients than the conventional methods, thereby allowing more improved water and nutrient use efficiencies and crop productivity.현재의 순환식 수경재배 시스템에서 양액의 분석과 보충은 전기전도도 (EC, electrical conductivity) 및 pH를 기반으로 수행되고 있으며, 양액의 공급은 작물의 생육 상태에 대한 고려 없이 항상 일정한 시간 동안 펌프가 동작하여 공급되는 형태이다. 그러나 EC 기반의 양액 관리는 개별 이온 농도의 동적인 변화를 감지할 수 없어 반복되는 보충 중 불균형이 발생하게 되어 양액의 폐기를 야기하며, 고정된 시간 동안의 양액 공급은 작물에 대해 과잉 또는 불충분한 물 공급으로 이어져 물 사용 효율의 저하를 일으킨다. 이러한 문제들에 대해, 개별 이온 농도에 대해 부족한 성분만을 선택적으로 보충하고, 작물의 생육 정도에 기반하여 필요한 수준에 맞게 양액을 공급하는 정밀 농업에 기반한 양액 관리를 수행하면 물과 비료 사용 효율의 향상과 양액의 재사용 기간 증진을 기대할 수 있다. 본 연구의 목적은 자동으로, 그리고 가변적으로 작물 생육 정보에 기반하여 양액 공급량을 제어하고, 작물 생장에 적합한 조성에 맞게 현재 양액의 이온 농도 센싱에 기반하여 적절한 수준만큼의 물과 개별 양분 비료를 보충할 수 있는 정밀 수경재배 양액 관리 시스템을 개발하는 것이다. 해당 목표를 달성하기 위해, 변이하는 물과 양분 요구량을 측정할 수 있는 모니터링 기술들을 분석하고 각 모니터링 기술들에 대한 검증을 수행하였다. 먼저, 작물의 물 요구량을 실시간으로 관측할 수 있는 영상 기반 측정 기술을 조사하였다. 영상 기반 분석 활용을 위해 박막경 기반의 순환식 수경재배 환경에서 자라는 상추의 이미지들을 전체 베드에 대해 수집할 수 있는 영상 모니터링 시스템을 구성하였고, 수집한 영상 중 상추 부분만을 excess green (ExG)과 Otsu 방법을 통해 분리하여 투영작물면적 (CC, canopy cover)을 획득하였다. 영상 처리 기술의 적용성 평가를 위해 직접 분석한 투영작물면적 값과 이를 비교하였다. 비교 검증 결과에서 투영작물면적 측정을 위한 영상 수집 및 분석이 수확 전까지의 상추에 대해 적용 가능함을 확인하였다. 이후 수집한 투영작물면적과 기온, 상대습도, 일사량을 기반으로 생육 중인 상추들이 요구하는 물의 양을 예측하기 위해 Penman-Monteith 방정식 기반의 증산량 예측 모델을 구성하였으며 실제 증산량과 비교하였을 때 높은 일치도를 확인하였다. 개별 이온 농도 측정과 관련하여서는, 이온선택성전극 (ISE, ion-selective electrode)를 이용한 수경재배 양액 내 이온의 연속적이고 자율적인 모니터링 수행을 위해 2점 정규화, 인공신경망, 그리고 이 둘을 복합적으로 구성한 하이브리드 신호 처리 기법의 성능을 비교하여 분석하였다. 분석 결과, 하이브리드 신호 처리 방식이 가장 높은 정확성을 보였으나, 센서 고장에 취약한 신경망 구조로 인해 장기간 모니터링 안정성에 있어서는 가장 높은 정밀도를 가진 2점 정규화 방식을 센서 어레이에 적용하는 것이 적합할 것으로 판단하였다. 또한, 주어진 개별 이온 농도 목표값에 맞는 비료 염 및 물의 최적 주입량을 결정하기 위해 의사결정트리 구조의 비료 투입 알고리즘을 제시하였다. 제시한 비료 투입 알고리즘의 효과에 대해서는 순차적인 목표에 대한 보충 및 특정 성분에 대해 집중적인 변화를 부여한 보충 수행 실험을 통해 검증하였으며, 그 결과 제시한 알고리즘은 주어진 목표값들에 따라 성공적으로 양액을 조성하였음을 확인하였다. 마지막으로, 제시되었던 센싱 및 제어 기술들을 통합하여 NFT 기반의 순환식 수경재배 배드에 상추 재배를 수행하여 실증하였다. 실증 실험에서, 종래의 고정 시간 양액 공급 대비 57.4%의 양액 공급량 감소와 상추 생육의 촉진을 확인하였다. 동시에, 개발 시스템은 NO3, K, Ca, Mg, 그리고 P에 대해 각각 4.9%, 1.4%, 3.2%, 5.2%, 그리고 14.9% 수준의 변동계수 수준을 보여 EC기반 보충 방식에서 나타난 변동계수 6.9%, 4.9%, 23.7%, 8.6%, 그리고 8.3%보다 대체적으로 우수한 이온 균형 유지 성능을 보였다. 이러한 결과들을 통해 개발 정밀 관비 시스템이 기존보다 효율적인 양액의 공급과 관리를 통해 양액 이용 효율성과 생산성의 증진에 기여할 수 있을 것으로 판단되었다.CHAPTER 1. INTRODUCTION 1 BACKGROUND 1 Nutrient Imbalance 2 Fertigation Scheduling 3 OBJECTIVES 7 ORGANIZATION OF THE DISSERTATION 8 CHAPTER 2. LITERATURE REVIEW 10 VARIABILITY OF NUTRIENT SOLUTIONS IN HYDROPONICS 10 LIMITATIONS OF CURRENT NUTRIENT SOLUTION MANAGEMENT IN CLOSED HYDROPONIC SYSTEM 11 ION-SPECIFIC NUTRIENT MONITORING AND MANAGEMENT IN CLOSED HYDROPONICS 13 REMOTE SENSING TECHNIQUES FOR PLANT MONITORING 17 FERTIGATION CONTROL METHODS BASED ON REMOTE SENSING 19 CHAPTER 3. ON-THE-GO CROP MONITORING SYSTEM FOR ESTIMATION OF THE CROP WATER NEED 21 ABSTRACT 21 INTRODUCTION 21 MATERIALS AND METHODS 23 Hydroponic Growth Chamber 23 Construction of an On-the-go Crop Monitoring System 25 Image Processing for Canopy Cover Estimation 29 Evaluation of the CC Calculation Performance 32 Estimation Model for Transpiration Rate 32 Determination of the Parameters of the Transpiration Rate Model 33 RESULTS AND DISCUSSION 35 Performance of the CC Measurement by the Image Monitoring System 35 Plant Growth Monitoring in Closed Hydroponics 39 Evaluation of the Crop Water Need Estimation 42 CONCLUSIONS 46 CHAPTER 4. HYBRID SIGNAL-PROCESSING METHOD BASED ON NEURAL NETWORK FOR PREDICTION OF NO3, K, CA, AND MG IONS IN HYDROPONIC SOLUTIONS USING AN ARRAY OF ION-SELECTIVE ELECTRODES 48 ABSTRACT 48 INTRODUCTION 49 MATERIALS AND METHODS 52 Preparation of the Sensor Array 52 Construction and Evaluation of Data-Processing Methods 53 Preparation of Samples 57 Procedure of Sample Measurements 59 RESULTS AND DISCUSSION 63 Determination of the Artificial Neural Network (ANN) Structure 63 Evaluation of the Processing Methods in Training Samples 64 Application of the Processing Methods in Real Hydroponic Samples 67 CONCLUSIONS 72 CHAPTER 5. DECISION TREE-BASED ION-SPECIFIC NUTRIENT MANAGEMENT ALGORITHM FOR CLOSED HYDROPONICS 74 ABSTRACT 74 INTRODUCTION 75 MATERIALS AND METHODS 77 Decision Tree-based Dosing Algorithm 77 Development of an Ion-Specific Nutrient Management System 82 Implementation of Ion-Specific Nutrient Management with Closed-Loop Control 87 System Validation Tests 89 RESULTS AND DISCUSSION 91 Five-stepwise Replenishment Test 91 Replenishment Test Focused on The Ca 97 CONCLUSIONS 99 CHAPTER 6. ION-SPECIFIC AND CROP GROWTH SENSING BASED NUTRIENT SOLUTION MANAGEMENT SYSTEM FOR CLOSED HYDROPONICS 101 ABSTRACT 101 INTRODUCTION 102 MATERIALS AND METHODS 103 System Integration 103 Implementation of the Precision Nutrient Solution Management System 106 Application of the Precision Nutrient Solution Management System to Closed Lettuce Soilless Cultivation 112 RESULTS AND DISCUSSION 113 Evaluation of the Plant Growth-based Fertigation in the Closed Lettuce Cultivation 113 Evaluation of the Ion-Specific Management in the Closed Lettuce Cultivation 118 CONCLUSIONS 128 CHAPTER 7. CONCLUSIONS 130 CONCLUSIONS OF THE STUDY 130 SUGGESTIONS FOR FUTURE STUDY 134 LIST OF REFERENCES 136 APPENDIX 146 A1. Python Code for Controlling the Image Monitoring and CC Calculation 146 A2. Ion Concentrations of the Solutions used in Chapter 4 (Unit: mg∙L−1) 149 A3. Block Diagrams of the LabVIEW Program used in Chapter 4 150 A4. Ion Concentrations of the Solutions used in Chapters 5 and 6 (Unit: mg∙L−1) 154 A5. Block Diagrams of the LabVIEW Program used in the Chapters 5 and 6 155 ABSTRACT IN KOREAN 160Docto

Application of upscaling methods for fluid flow and mass transport in multi-scale heterogeneous media : A critical review

Physical and biogeochemical heterogeneity dramatically impacts fluid flow and reactive solute transport behaviors in geological formations across scales. From micro pores to regional reservoirs, upscaling has been proven to be a valid approach to estimate large-scale parameters by using data measured at small scales. Upscaling has considerable practical importance in oil and gas production, energy storage, carbon geologic sequestration, contamination remediation, and nuclear waste disposal. This review covers, in a comprehensive manner, the upscaling approaches available in the literature and their applications on various processes, such as advection, dispersion, matrix diffusion, sorption, and chemical reactions. We enclose newly developed approaches and distinguish two main categories of upscaling methodologies, deterministic and stochastic. Volume averaging, one of the deterministic methods, has the advantage of upscaling different kinds of parameters and wide applications by requiring only a few assumptions with improved formulations. Stochastic analytical methods have been extensively developed but have limited impacts in practice due to their requirement for global statistical assumptions. With rapid improvements in computing power, numerical solutions have become more popular for upscaling. In order to tackle complex fluid flow and transport problems, the working principles and limitations of these methods are emphasized. Still, a large gap exists between the approach algorithms and real-world applications. To bridge the gap, an integrated upscaling framework is needed to incorporate in the current upscaling algorithms, uncertainty quantification techniques, data sciences, and artificial intelligence to acquire laboratory and field-scale measurements and validate the upscaled models and parameters with multi-scale observations in future geo-energy research.© 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)This work was jointly supported by the National Key Research and Development Program of China (No. 2018YFC1800900 ), National Natural Science Foundation of China (No: 41972249 , 41772253 , 51774136 ), the Program for Jilin University (JLU) Science and Technology Innovative Research Team (No. 2019TD-35 ), Graduate Innovation Fund of Jilin University (No: 101832020CX240 ), Natural Science Foundation of Hebei Province of China ( D2017508099 ), and the Program of Education Department of Hebei Province ( QN219320 ). Additional funding was provided by the Engineering Research Center of Geothermal Resources Development Technology and Equipment , Ministry of Education, China.fi=vertaisarvioitu|en=peerReviewed

Scientific research trends for plant factory with artificial lighting: scoping review

Plant Factory With Artificial Lighting consists of a protected horticulture system in controlled environment facilities, in combination with various levels of growing surface and factors such as lighting, cultivation system, crop nutrition, and energy efficiency. The objective of this study was to identify in published scientific articles the current topics addressed, the potentialities and challenges identified, and their future position on the this system. This is a scoping review of 49 articles published in scientific journals that answered the research question “What are the topics addressed in the Journal Article on Plant Factory With Artificial Lighting?” from 2015 to 2022. The reviewed articles demonstrated that the development of alternatives for cultivation methods, lighting systems with variation of light spectrum, irrigation systems, and new technologies for the production chain, aimed at increasing production capacity, is a trend. They also indicated that, although the Plant Factory With Artificial Lightning has shown potential for the production of several crops, technical and economic optimization requires greater attention, pointing out that technological development and production methods are fundamental factors to establish the system as an alternative of agricultural production in sustainable urban centers.A Plant Factory With Artificial Lighting (PFAL) consiste em um sistema de horticultura protegido em instalações de ambiente controlado, em combinação com vários níveis de superfície de crescimento e associação de fatores como iluminação, sistema de cultivo, nutrição das culturas e eficiência energética. O objetivo deste estudo foi identificar nos artigos científicos publicados os atuais temas abordados, as potencialidades e desafios identificados e seu posicionamento futuro sobre as PFAL. Trata-se de uma revisão de escopo de 49 artigos publicados em periódicos científicos que davam a resposta à pergunta de investigação, “Quais são os temas abordados em artigos científicos sobre PFAL?”, no período de 2015 a 2022. Os artigos revisados demonstraram como tendência o desenvolvimento de alternativas para os métodos de cultivo, sistemas de iluminação com variação do espectro de luz, sistemas de irrigação e novas tecnologias de cadeia produtiva, visando ao aumento da capacidade produtiva. Também mostraram que, embora a PFAL tenha demonstrado potencial para a produção de diversas culturas, a otimização técnica e econômica requer maior atenção, apontando-se que o desenvolvimento tecnológico e os métodos produtivos são fatores fundamentais para ela se estabelecer como alternativa de produção agrícola em centros urbanos sustentáveis

Modeling and optimization of environment in agricultural greenhouses for improving cleaner and sustainable crop production

Resource-use efficiency and crop yield are significant factors in the management of agricultural greenhouse. Appropriate modeling methods effectively improve the control performance and efficiency of the greenhouse system and are conducive to the design of water and energy-saving strategies. Meanwhile, the extreme environment could be forecasted in advance, which reduces pests and diseases as well as provides high-quality food. Accordingly, the interest of the scientific community in greenhouse modeling and optimizing has grown considerably. The objective of this work is to provide guidance and insight into the topic by reviewing 73 representative articles and to further support cleaner and sustainable crop production. Compared to the existing literature review, this work details the approaches to improve the greenhouse model in the aspects of parameter identification, structure and process optimization, and multi-model integration to better model complex greenhouse system. Furthermore, a statistical study has been carried out to summarize popular technology and future trends. It was found that dynamic and neural network techniques are most commonly used to establish the greenhouse model and the heuristic algorithm is popular to improve the accuracy and generalization ability of the model. Notably, deep learning, the combination of “knowledge” and “data”, and coupling between the greenhouse system elements have been considered as future valuable development