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Enhancing aquaponics management with IoT-based Predictive Analytics for efficient information utilization

Information Processing in Agriculture 2019年第3期6卷 375-385页

作者： Divas Karimanzira thomas rauschenbach Dept of Surface and Maritime Systems Fraunhofer I0SB-ASTIlmenauAm Vogelherd 5098689 IlmenauGermany

Modern aquaponic systems can be highly successful,but they require intensive monitoring,control and ***,the Automation Pyramid(AP)with its layers of Supervisory Control and Data Acquisition(SCADA),Enterprise Resource Planning(ERP)and Manufacturing Execution System(MES)is applied for process *** cloudbased IoT-based Predictive Analytics at the fore marsh,it is worth finding out if IoTwill make these technologies obsolete,or they can work together to gain more beneficial *** this paper,we will discuss the enhancement of SCADA,ERP and MES with IoT in aquaponics and likewise how IoT-based Predictive Analytics can help to get more out of *** example use case of an aquaponics project with five demonstration sites in different geographical locations will be presented to show the benefits of IoT on example Predictive Analytics *** is the collection of data from the five demonstration sites over IoT to make the models of fish,tomatoes,technical components such as filters used for remote monitoring,predictive remote maintenance and economical optimization of the individual plants *** of the various models,fish and crop growth models,models for econometric optimization were evaluated using Monte Carlo Simulations revealing as expected the superiority of the IoT-based *** analysis suggest that the models are generally tolerant to the temperature coefficient variations of up to 15%and the econometric models tolerated a variation of for example feed ration size for fish of up to 4%and by the energy optimization models a tolerance of up to 14%by variations of solar radiation could be ***,from the analysis made,it can be concluded that MES has several capabilities which cannot be replaced by IoT such as responsiveness to trigger changes on *** act as proxy when there is no case for sensors and reliably ensure correct execution in the aquaponics *** systems can produce unpreced

关键词： Aquaponics Automation pyramid IoT Predictive analytics Big Data

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Integrated navigation for autonomous underwater vehicles in aquaculture: A review

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Information Processing in Agriculture 2020年第1期7卷 139-151页

作者： Jianhua Bao Daoliang Li Xi Qiao thomas rauschenbach Beijing Engineering and Technology Research Center for Internet of Things in Agriculture China Agricultural UniversityBeijing 100083PR China College of Information and Electrical Engineering China Agricultural UniversityBeijing 100083PR China School of Electrical Engineering and Automation Jiangsu Normal UniversityXuzhou 221116PR China Fraunhofer Center for Applied Systems Technology Am Vogelherd 5098693 IlmenauGermany

Aquaculture is the world’s fastest growing sector within the food industry,supplying humans with over half their aquatic *** quality monitoring or cage inspection is an indispensable part in aquaculture and is usually done *** underwater vehicles(AUVs)are increasingly being used in aquaculture as technology advances and the cost *** navigation is considered as a basic function of AUVs but is a challenging issue primarily due to the attenuated nature of electromagnetic waves in water and unstructured underwater *** inertial navigation system(INS)is usually selected as the core navigation equipment for AUV navigation because it never fails to *** paper reviews and surveys the latest advances in integrated navigation technologies for AUVs and provides a comprehensive reference for researchers who intend to apply AUVs to autonomous monitoring of *** INS has difficulty obtaining long-range precision navigation due to the inherent error accumulation of inertial sensors over time;aiding inertial navigation systems with auxiliary sensors are common means to improve the navigation accuracy of an INS for *** survey is conducted according to different assisted navigation technologies for inertial ***,the future challenges of the AUV navigation are also presented.

关键词： Aquaculture Underwater navigation Autonomous underwater vehicle (AUV) Inertial navigation system(INS) Integrated navigation

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Deep Learning Based Model Predictive Control for a Reverse Osmosis Desalination Plant

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Journal of Applied Mathematics and Physics 2020年第12期8卷 2713-2731页

作者： Divas Karimanzira thomas rauschenbach Department of Surface Water and Maritime Systems Fraunhofer IOSB-AST Ilmenau Germany

Reverse Osmosis (RO) desalination plants are highly nonlinear multi-input-multioutput systems that are affected by uncertainties, constraints and some physical phenomena such as membrane fouling that are mathematically difficult to describe. Such systems require effective control strategies that take these effects into account. Such a control strategy is the nonlinear model predictive (NMPC) controller. However, an NMPC depends very much on the accuracy of the internal model used for prediction in order to maintain feasible operating conditions of the RO desalination plant. Recurrent Neural Networks (RNNs), especially the Long-Short-Term Memory (LSTM) can capture complex nonlinear dynamic behavior and provide long-range predictions even in the presence of disturbances. Therefore, in this paper an NMPC for a RO desalination plant that utilizes an LSTM as the predictive model will be presented. It will be tested to maintain a given permeate flow rate and keep the permeate concentration under a certain limit by manipulating the feed pressure. Results show a good performance of the system.

关键词： Desalination Model Predictive Control Artificial Intelligence Long Short Term Memory Neural Network Reverse Osmosis

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Performance Prediction of a Reverse Osmosis Desalination System Using Machine Learning

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Journal of Geoscience and Environment Protection 2021年第7期9卷 46-61页

作者： Divas Karimanzira thomas rauschenbach Department of Surface Water and Maritime Systems Fraunhofer IOSB Ilmenau Germany

One of the major challenges that membrane manufacturers, commercial enterprises and the scientific community in the field of membrane-based filtration or reverse osmosis (RO) desalination have to deal with is system performance retardation due to membrane fouling. In this respect, the prediction of fouling or system performance in membrane-based systems is the key to determining the mid and long-term plant operating conditions and costs. Despite major research efforts in the field, effective methods for the estimation of fouling in RO desalination plants are still in infancy, for example, most of the existing methods, neither consider the characteristics of the membranes such as the spacer geometry, nor the efficiency and the day to day chemical cleanings. Furthermore, most studies focus on predicting a single fouling indicator, e.g., flux decline. Faced with the limits of mathematical or numerical approach, in this paper, machine learning methods based on Multivariate Temporal Convolutional Neural networks (MTCN), which take into account the membrane characteristics, feed water quality, RO operation data and management practice such as Cleaning In Place (CIP) will be considered to predict membrane fouling using measurable multiple indicators. The temporal convolution model offers one the capability to explore the temporal dependencies among a remarkably long historical period and has potential use for operational diagnostics, early warning and system optimal control. Data collected from a Desalination RO plant will be used to demonstrate the capabilities of the prediction system. The method achieves remarkable predictive accuracy (root mean square error) of 0.023

关键词： Reverse Osmosis Membrane Fouling Fouling Indices Predicting Models Machine Learning Multivariate Temporal Convolutional Neural Networks

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Optimal Utilization of Renewable Energy in Aquaponic Systems

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Energy and Power Engineering 2018年第6期10卷 279-300页

作者： Divas Karimanzira thomas rauschenbach Department of Surface Water and Maritime Systems Fraunhofer I0SB-AST Ilmenau Germany

Aquaponic systems require energy in different forms, heat, solar radiation, electricity etc. Typical actuator components of an aquaponic system include pumps, aerators, heaters, coolers, feeders, propagators, lights, etc., which need electrical energy to operate. Hybrid Energy Systems (HES) can help in improving the economic and environmental sustainability of aquaponic systems with respect to energy aspects. Energy management is one of the key issues in operating the HES, which needs to be optimized with respect to the current and future change in generation, demand, and market price, etc. In this paper, a Decision Support System (DSS) for optimal energy management of an aquaponic system that integrates different energy sources and storage mechanisms according to priorities will be presented. The integrated model consists of photovoltaic and solar thermal modules, wind turbine, hydropower, biomass plant, CHP, gas boiler, energy and heat storage systems and access to the power grid and district heating. The results show that the proposed method can significantly increase the utilization of HES and reduce the exchange with the power grid and district heating and consequently reduce running costs.

关键词： Aquaponics Renewable Energy Modeling Network Flow Optimization

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基于结构方程模型的水利工程社会影响路径

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水利经济 2017年第1期35卷 26-30页

作者：贺正齐黄德春马智杰 thomas rauschenbach 河海大学商学院江苏南京211100 江苏省“世界水谷”与水生态文明协同创新中心江苏南京211100 中国水利水电科学研究院北京100038 德国Fraunhofer IOSB Ilmenau98693

以水利工程产生的社会影响为研究对象,在确定水利工程社会影响变量的基础上构建水利工程社会影响的结构方程模型,比较水利工程的社会影响路径。以富江小水电代燃料工程为例进行实证,结果表明:富江小水电代燃料工程对家庭结构、人文景观... 详细信息

以水利工程产生的社会影响为研究对象,在确定水利工程社会影响变量的基础上构建水利工程社会影响的结构方程模型,比较水利工程的社会影响路径。以富江小水电代燃料工程为例进行实证,结果表明:富江小水电代燃料工程对家庭结构、人文景观以及个人收入产生的影响较大,在水利工程项目评价中应特别注重这些方面的影响。

关键词：水利工程小水电代燃料社会影响结构方程模型影响路径

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