Smart Sensing with Edge Computing in Precision Agriculture for Soil Assessment and Heavy Metal Monitoring: A Review

With the implementation of the Internet of Things, the agricultural domain has become data-driven, allowing for well-timed and cost-effective farm management while remaining environmentally sustainable. Thus, the incorporation of Internet of Things in the agricultural domain is the need of the hour for developing countries whose gross domestic product primarily depends on the farming sector. It is worth highlighting that developing nations lack the infrastructure for precision agriculture; therefore, it has become necessary to come up with a methodological paradigm which can accommodate a complete model to connect ground sensors to the compute nodes in a cost-effective way by keeping the data processing limitations and constraints in consideration. In this regard, this review puts forward an overview of the state-of-the-art technologies deployed in precision agriculture for soil assessment and pollutant monitoring with respect to heavy metal in agricultural soil using various sensors. Secondly, this manuscript illustrates the processing of data generated from the sensors. In this regard, an optimized method of data processing derived from cloud computing has been shown, which is called edge computing. In addition to this, a new model of high-performance-based edge computing is also shown for efficient offloading of data with smooth workflow optimization. In a nutshell, this manuscript aims to open a new corridor for the farming sector in developing nations by tackling challenges and providing substantial consideration.

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Advanced UAV–WSN System for Intelligent Monitoring in Precision Agriculture

Sensors ◽

10.3390/s20030817 ◽

2020 ◽

Vol 20 (3) ◽

pp. 817 ◽

Cited By ~ 9

Author(s):

Dan Popescu ◽

Florin Stoican ◽

Grigore Stamatescu ◽

Loretta Ichim ◽

Cristian Dragana

Keyword(s):

Data Collection ◽

Data Processing ◽

Precision Agriculture ◽

High Performance ◽

New Technologies ◽

Control Analysis ◽

Online Data ◽

Monitoring Point ◽

High Productivity ◽

In Situ Data

The growing need for food worldwide requires the development of a high-performance, high-productivity, and sustainable agriculture, which implies the introduction of new technologies into monitoring activities related to control and decision-making. In this regard, this paper presents a hierarchical structure based on the collaboration between unmanned aerial vehicles (UAVs) and federated wireless sensor networks (WSNs) for crop monitoring in precision agriculture. The integration of UAVs with intelligent, ground WSNs, and IoT proved to be a robust and efficient solution for data collection, control, analysis, and decisions in such specialized applications. Key advantages lay in online data collection and relaying to a central monitoring point, while effectively managing network load and latency through optimized UAV trajectories and in situ data processing. Two important aspects of the collaboration were considered: designing the UAV trajectories for efficient data collection and implementing effective data processing algorithms (consensus and symbolic aggregate approximation) at the network level for the transmission of the relevant data. The experiments were carried out at a Romanian research institute where different crops and methods are developed. The results demonstrate that the collaborative UAV–WSN–IoT approach increases the performances in both precision agriculture and ecological agriculture.

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Smart metering system data analytics platform using multicore edge computing

International Journal of Reconfigurable and Embedded Systems (IJRES) ◽

10.11591/ijres.v10.i1.pp11-17 ◽

2021 ◽

Vol 10 (1) ◽

pp. 11

Author(s):

Juan C. Olivares-Rojas ◽

Enrique Reyes-Archundia ◽

José A. Gutiérrez-Gnecchi ◽

Ismael Molina-Moreno ◽

Adriana C. Téllez-Anguiano ◽

...

Keyword(s):

Internet Of Things ◽

Smart Grid ◽

Data Processing ◽

Data Analytics ◽

Electricity Consumption ◽

Edge Computing ◽

Smart Meter ◽

Smart Metering ◽

Smart Meters ◽

System Data

The smart grid revolution has only been possible, thanks to the development and proliferation of smart meters. The increasingly growing computing capabilities for Internet of Things devices have made it possible for data to be processed directly from the devices where it is produced; this has been called edge computing. Edge computing is allowing the smart grid to become increasingly intelligent to solve problems that make electricity consumption more efficient and environmentally friendly. This work presents the implementation of a smart metering system that allows data analytics using a multiprocessing architecture directly on the smart meter. The results show that the development of smart meters with data analytics capabilities at the edge is a reality today, and the use of multiprocessing permits the improvement of data processing.

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A GIS-Based Early Warning and Emergency Decision Support System for River Heavy Metal Pollution Incidents

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.664.399 ◽

2013 ◽

Vol 664 ◽

pp. 399-402

Author(s):

Yuan Hua Chen ◽

Ji Ping Jiang ◽

Yu Liu ◽

Li Na Zhang ◽

Yi Wang

Keyword(s):

Heavy Metal ◽

Emergency Response ◽

Early Warning ◽

Metal Pollution ◽

Heavy Metal Pollution ◽

Cost Effective ◽

Heavy Metal Accumulation ◽

Source Information ◽

Emergency Decision ◽

Metal Monitoring

Recently, aquatic pollution of heavy metals has been breaking out with increasing frequency around the world, which puts great threats to ecosystem and human health. However, there are seldom researches on Early Warning/Emergency Response System (EWERS) of heavy metal pollution. In this present study, we propose a logistic structure and function structure of EWERS on the ground of functional requirement of response to river heavy metal pollution. This system includes five subsystems: heavy metal monitoring, contaminant source information management, emergency management, database and authority management subsystems. It can not only predict the process of heavy metal accumulation processes, but also calculate risk degree for given area taking the water function zone into consideration. For those areas where risk is identified as unacceptable, emergency response plan should be created by case base reasoning to achieve reduction hazard in a cost-effective way.

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Analisis Kinerja Jaringan Sensor Nirkabel untuk Edge Computing Menggunakan LORA SX1278

Jurnal Teknologi Informasi dan Ilmu Komputer ◽

10.25126/jtiik.2021853631 ◽

2021 ◽

Vol 8 (5) ◽

pp. 887

Author(s):

Mochammad Hannats Hanafi Ichsan

Keyword(s):

Internet Of Things ◽

Data Processing ◽

Large Data ◽

Edge Computing ◽

Communication Process ◽

Smart System ◽

Machine To Machine ◽

Smart Systems ◽

Mesh Topology ◽

The Internet Of Things

Jaringan Sensor Nirkabel (WSN) adalah salah satu teknologi yang muncul untuk proses deploy dari Internet of Things, Smart System, Machine to Machine networks dan lain sebagainya. Dimana setiap node dari WSN tersebut memiliki kemampuan untuk sensing, komputasi hinga proses pengiriman data. Pemrosesan data secara umum dilakukan pada Cloud atau node lain, hal ini menyebabkan beban kerja dari node lain atau Cloud tersebut menjadi cukup berat. Proses sensing dapat dilakukan dengan menggunakan berbagai sensor sesuai kebutuhan, sedangkan teknologi untuk pemrosesan pada node sensing disebut dengan teknologi Edge Computing. Konsep dari Edge Computing adalah bagaimana sebuah node bisa berpikir untuk menyelesaikan masalah atau mengambil keputusan. Kemudian data hasil pengolahan tersebut dikirimkan ke node yang lain untuk diolah lebih lanjut sehingga kinerja dari node lain atau Cloud lebih ringan. Salah satu teknologi dalam pengiriman data yang dapat dipergunakan dengan baik dan kemampuan jarak komunikasinya cukup panjang adalah LoRa. Salah satu topologi untuk WSN yang dinilai sangat baik untuk pengiriman data adalah Mesh, dimana seluruh node dapat berkomunikasi dengan baik. Oleh karena itu pada penelitian ini akan difokuskan untuk melakukan analisis kemampuan LoRa dalam pengiriman data berdasarkan jarak dan besar data. Karena pada implementasinya jarak berdasarkan besar data hasil pengolahan dari Edge Computing cukup bervariasi. Sehingga pada penelitian ini menghasilkan studi kelayakan LoRa sebagai perangkat untuk proses komunikasi pada WSN menggunakan topologi Mesh. Berdasarkan hasil penelitian yang dilakukan secara keseluruhan LoRa cukup baik untuk pengiriman data hingga 256 bytes dan jarak 300 meter berdasarkan delay, throughput, RSSI dan SNR sehingga sangat layak untuk diimplementasikan pada Edge Computing. AbstractWireless Sensor Networks (WSN) is one of the emerging technologies for the deployment of the Internet of Things, Smart Systems, Machine to Machine networks and so on. Where each node of the WSN has the ability to sensing, computation until the process of sending data. Data processing is generally done on the Cloud or other nodes, this causes the workload of other nodes or the Cloud to be quite heavy. The sensing process can be done by using various sensors as needed, while the technology for processing the sensing node is called Edge Computing technology. The concept of Edge Computing is how a node can think to solve a problem or make a decision. Then the processing data is sent to another node for further processing so that the performance of other nodes or the Cloud is lighter. One of the technologies in sending data that can be used properly and the ability of its long communication distance is LoRa. One of the topologies for WSN that is considered very good for sending data is Mesh, where all nodes can communicate well. Therefore this research will focus on analyzing the ability of LoRa in sending data based on distance and data size. Because in the implementation of the distance based on the large data processing results from Edge Computing is quite varied. So that this research resulted in a feasibility study of LoRa as a device for the communication process at WSN using Mesh topology. Based on the results of research conducted overall LoRa is good enough for sending data up to 256 bytes and a distance of 300 meters based on delay, throughput, RSSI and SNR so it is very feasible to be implemented on Edge Computing.

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Information Detection and Data Denoising Method Using Nano Electrode Array Sensor

Journal of Nanoelectronics and Optoelectronics ◽

10.1166/jno.2021.2958 ◽

2021 ◽

Vol 16 (2) ◽

pp. 303-311

Author(s):

Cheng Le

Keyword(s):

Heavy Metal ◽

Gold Nanoparticles ◽

Data Processing ◽

Equivalent Circuit ◽

Electrode Array ◽

Electrode Polarization ◽

Wavelet Domain ◽

Denoising Method ◽

Array Sensor ◽

Metal Monitoring

Computer technology and sensor technology can be combined. The technology set can be used to monitor the concentration of heavy metals in soil, which can help to prevent the occurrence of heavy metal pollution in time. First, nanotechnology, electrode polarization and the advantages of gold nanoparticles modified electrode are studied, and the design method of the nano electrode array is further analyzed. Also, the internal parameters of the three-electrode equivalent circuit are studied, and the model of the three-electrode equivalent circuit is derived. On this basis, a heavy metal monitoring circuit based on the nano electrode array sensor is designed. While the information monitoring based on this circuit is performed, wavelet domain denoising technology is studied in data processing. In view of the defects of the general hard threshold in practical application, the threshold is improved to recognize the depth of denoising. In the experiment, gold nanoparticles modified mercury electrode is used as working electrode. According to the principle that the precipitation time is inversely proportional to the detection current, 0.01 mol/L HCl is selected as the solution environment; moreover, it is set that pH=4 and the precipitation time is 4 min. The results show that for the same kind of ions, with the increase of the concentration of ions to be measured, the scanning potential range remains unchanged, while the peak current increases significantly. Metal ions can be effectively identified based on the potential corresponding to peak value. In the data processing of the detection circuit, the improved signal denoising method is compared with the default threshold wavelet domain denoising technology. The results show that the improved wavelet domain denoising method has less signal error, and the denoising effect of heavy metal detection is obvious.

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Performance of the ATMOS41 All-in-One Weather Station for Weather Monitoring

Sensors ◽

10.3390/s21030741 ◽

2021 ◽

Vol 21 (3) ◽

pp. 741

Author(s):

Olga Dombrowski ◽

Harrie-Jan Hendricks Franssen ◽

Cosimo Brogi ◽

Heye Reemt Bogena

Keyword(s):

Low Income ◽

Precision Agriculture ◽

High Performance ◽

Low Cost ◽

Urban Climate ◽

Regression Function ◽

Cost Effective ◽

Reference Station ◽

Small Scale ◽

Weather Station

Affordable and accurate weather monitoring systems are essential in low-income and developing countries and, more recently, are needed in small-scale research such as precision agriculture and urban climate studies. A variety of low-cost solutions are available on the market, but the use of non-standard technologies raises concerns for data quality. Research-grade all-in-one weather stations could present a reliable, cost effective solution while being robust and easy to use. This study evaluates the performance of the commercially available ATMOS41 all-in-one weather station. Three stations were deployed next to a high-performance reference station over a three-month period. The ATMOS41 stations showed good performance compared to the reference, and close agreement among the three stations for most standard weather variables. However, measured atmospheric pressure showed uncertainties >0.6 hPa and solar radiation was underestimated by 3%, which could be corrected with a locally obtained linear regression function. Furthermore, precipitation measurements showed considerable variability, with observed differences of ±7.5% compared to the reference gauge, which suggests relatively high susceptibility to wind-induced errors. Overall, the station is well suited for private user applications such as farming, while the use in research should consider the limitations of the station, especially regarding precise precipitation measurements.

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Mineral/microfibrillated cellulose composite materials: High performance products, applications, and product forms

TAPPI Journal ◽

10.32964/tj17.09.507 ◽

2018 ◽

Vol 17 (09) ◽

pp. 507-515 ◽

Cited By ~ 1

Author(s):

David Skuse ◽

Mark Windebank ◽

Tafadzwa Motsi ◽

Guillaume Tellier

Keyword(s):

Composite Materials ◽

High Performance ◽

Aqueous Suspension ◽

Production Capacity ◽

Cost Savings ◽

Cost Effective ◽

New Materials ◽

Wet Strength ◽

Product Forms ◽

Cellulose Composite

When pulp and minerals are co-processed in aqueous suspension, the mineral acts as a grinding aid, facilitating the cost-effective production of fibrils. Furthermore, this processing allows the utilization of robust industrial milling equipment. There are 40000 dry metric tons of mineral/microfbrillated (MFC) cellulose composite production capacity in operation across three continents. These mineral/MFC products have been cleared by the FDA for use as a dry and wet strength agent in coated and uncoated food contact paper and paperboard applications. We have previously reported that use of these mineral/MFC composite materials in fiber-based applications allows generally improved wet and dry mechanical properties with concomitant opportunities for cost savings, property improvements, or grade developments and that the materials can be prepared using a range of fibers and minerals. Here, we: (1) report the development of new products that offer improved performance, (2) compare the performance of these new materials with that of a range of other nanocellulosic material types, (3) illustrate the performance of these new materials in reinforcement (paper and board) and viscosification applications, and (4) discuss product form requirements for different applications.

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Parallel Computing for Tire Simulations

Tire Science and Technology ◽

10.2346/1.3637743 ◽

2011 ◽

Vol 39 (3) ◽

pp. 193-209 ◽

Cited By ~ 2

Author(s):

H. Surendranath ◽

M. Dunbar

Keyword(s):

High Performance ◽

Effective Means ◽

Cost Effective ◽

Turnaround Time ◽

Careful Consideration ◽

Rolling Contact ◽

Element Analysis ◽

Parallel Solvers ◽

Design Changes ◽

Highly Nonlinear

Abstract Over the last few decades, finite element analysis has become an integral part of the overall tire design process. Engineers need to perform a number of different simulations to evaluate new designs and study the effect of proposed design changes. However, tires pose formidable simulation challenges due to the presence of highly nonlinear rubber compounds, embedded reinforcements, complex tread geometries, rolling contact, and large deformations. Accurate simulation requires careful consideration of these factors, resulting in the extensive turnaround time, often times prolonging the design cycle. Therefore, it is extremely critical to explore means to reduce the turnaround time while producing reliable results. Compute clusters have recently become a cost effective means to perform high performance computing (HPC). Distributed memory parallel solvers designed to take advantage of compute clusters have become increasingly popular. In this paper, we examine the use of HPC for various tire simulations and demonstrate how it can significantly reduce simulation turnaround time. Abaqus/Standard is used for routine tire simulations like footprint and steady state rolling. Abaqus/Explicit is used for transient rolling and hydroplaning simulations. The run times and scaling data corresponding to models of various sizes and complexity are presented.

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