Smart Field Research Articles

Design strategy research on active interactive system for household appliances based on artificial intelligence

In the era of artificial intelligence, active interaction has become an emerging design and development trend, bringing many opportunities and possibilities to the system innovation and experience upgrade of intelligent household appliances. This research firstly analyzed and sorted out documents in related fields such as human-agent active interaction, interaction design in intelligent household appliances and user-centered interaction design, combined with active interaction cases at home and abroad as well as other smart life fields. According to the system process and operating mode, the interaction stages of “perception-display-control-understanding” were divided. And the connotation, performance, valve and opportunity points of design intervention and opportunity points of active interaction in each stage were further analyzed. Finally, this research constructed a smart refrigerator active interaction strategy from the user’s perspective, from the four levels of user needs that are knowable, visible, controllable, and predictable, which could realize the trust relationship of man-machine collaboration and an orderly and active interaction system.

Electronic control of water resources using smart field irrigation systems

<span>Most </span><span>of the research </span><span>showed that the reason behind the agricultural lesions is the over usage of water in irrigation the matter which cause the appearance of fungicide on plants and salinity of the soil. From this point emerged the need for adapt some systems to work in farms in order to reduces the expenses of the product, improve its quality and lessen the consumption of water. Internet webs have been a preceding means in such a scope; and they also showed flexibility in designing such systems. In this paper; a smart irrigation system that depend on the values of moisture content and the agricultural constants (Feld Capacity, Wilt Point of the plant, Bulk Density</span><span>, Depth of the root of the plant, the consumption of each water dripper and the passing area) in making the decision of irrigation and running the water pump, depending on the quantity of water to be added and the duration of irrigation time,</span><span> and it is better. Field humidity levels at 0.32</span><span>. This system was built by using the microcontroller ESP-32S&ESP8266 and moister sensor. The data was uploaded to Adafruit server for the sake of remote monitoring by MQTT protocol.</span>

Foot Gesture Recognition Using High-Compression Radar Signature Image and Deep Learning.

Recently, Doppler radar-based foot gesture recognition has attracted attention as a hands-free tool. Doppler radar-based recognition for various foot gestures is still very challenging. So far, no studies have yet dealt deeply with recognition of various foot gestures based on Doppler radar and a deep learning model. In this paper, we propose a method of foot gesture recognition using a new high-compression radar signature image and deep learning. By means of a deep learning AlexNet model, a new high-compression radar signature is created by extracting dominant features via Singular Value Decomposition (SVD) processing; four different foot gestures including kicking, swinging, sliding, and tapping are recognized. Instead of using an original radar signature, the proposed method improves the memory efficiency required for deep learning training by using a high-compression radar signature. Original and reconstructed radar images with high compression values of 90%, 95%, and 99% were applied for the deep learning AlexNet model. As experimental results, movements of all four different foot gestures and of a rolling baseball were recognized with an accuracy of approximately 98.64%. In the future, due to the radar’s inherent robustness to the surrounding environment, this foot gesture recognition sensor using Doppler radar and deep learning will be widely useful in future automotive and smart home industry fields.

Internet of Things based Smart Irrigation Control System for Paddy Field

This study aimed to establish a water-saving irrigation technique-based Smart Field Cultivation Server (SFCS) for paddy field irrigation by employing information and communication technologies. The development of SFCS considered the requirement on rice growth, pest development, and fieldwork management. The proposed SFCS is equipped with a solar power supply system and consisted of sensors including illumination, air temperature, air humidity, water level, soil moisture content, soil electronic conductivity, and soil temperature. Narrowband Internet of Things (NB-IoT) is used for data transmission due to the data size and transmitting frequency. A smartphone-based application (APP) has been developed for users to monitor field environment by tabular, dashboard panel, and whisker chart box, provides multiple data display ways for different purposes. Moreover, a proposal for a water-saving irrigation technique named system of probiotics rice intensification (SPRI) has been integrated into the APP. With the developed APP, farmers will receive fieldwork reminders by calendar day that water-saving irrigation may be possibly implemented. The SFCS is not only shown ability on the field monitoring but also links the gap between the fieldwork application and modern technology.

BIM for Smart Hospital Management during COVID-19 Using MCDM

In context of the recent COVID-19 pandemic, smart hospitals’ contributions to pre-medical, remote diagnosis, and social distancing has been further vetted. Smart hospital management evolves with new technology and knowledge management, which needs an evaluation system to prioritize its associated criteria and sub-criteria. The global effect of the COVID-19 pandemic further necessitates a comprehensive research of smart hospital management. This paper will utilize Analytical Hierarchy Process (AHP) within Multiple Criteria Decision Making (MCDM) to establish a smart hospital evaluation system with evaluation criteria and sub-criteria, which were then further prioritized and mapped to BIM-related alternatives to inform asset information management (AIM) practices. This context of this study included the expert opinions of six professionals in the smart hospital field and collected 113 responses from hospital-related personnel. The results indicated that functionalities connected to end users are critical, in particular IoT’s Network Core Functionalities, AI’s Deep Learning and CPS’s Special Network Technologies. Furthermore, BIM’s capability to contribute to the lifecycle management of assets can relate and contribute to the asset-intensive physical criteria of smart hospitals, in particular IoT, service technology innovations and their sub-criteria.

Sunlight‐Responsive Photothermochromic Fabric with Reversible Color Changing Based on Photothermal Conversion

Intelligent color‐changing textiles have attracted increasing attention due to their potential application in healthcare monitoring and artificial intelligence. To realize the active modulation of color via sunlight, the photothermochromic fabric that adjusts its color based on the photothermal conversion performance of the sunlight‐responsive heating layer under irradiation of solar is fabricated by double‐side coating. Depending on the light absorption at 350–2500 nm, the sunlight‐responsive photothermochromic fabric (SPTCF) exposed under the irradiation power density of 500 W m−2 for 4 min displays efficient photothermal conversion, resulting in the increase in temperature from room temperature (23.0 °C) to above 47.0 °C. Simultaneously, the color of SPTCF changes from blue to white and returns to blue once the light is turned off for 3 min, indicating the sensitive and reversible photothermochromic property of the SPTCF. Compared with the contrast layer, the sunlight‐responsive heating layer exhibits a rapid photothermal conversion speed and high optical contrast under the same irradiation condition. The heating/cooling curves show steady signals after mechanical deformations and 150 cycles, revealing the favorable durability of the SPTCF under the solar irradiation. The sensitive photothermochromic properties promote the application of the SPTCF in smart wearable fields.

Operator Develops Fully Smart Onshore Field

This article, written by JPT Technology Editor Judy Feder, contains highlights of paper SPE 203461, “Digitalization in the Oil and Gas Industry—A Case Study of a Fully Smart Field in the United Arab Emirates,” by Muhammad Arif and Abdulla Mohammed Al Senani, ADNOC, prepared for the 2020 Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, held virtually from 9–12 November. The paper has not been peer reviewed. One of the first oil fields in the UAE to be fully operated remotely is in the southeast region, 250 km from Abu Dhabi. The complete paper discusses the development and commissioning of the field, which is the first smart field for ADNOC Onshore. The designed and applied technology facilitated unmanned operation of the field from downhole to export. Introduction Oilfield digitalization encompasses gathering real-time and non-real-time data from wells, flow lines, manifolds, stations, and water injection facilities; analysis of the data using algorithms, flowcharts, plots, and reports; and user access to this data on user-friendly screens. This allows engineers to focus on interpretation of data vs. searching, organizing, and formatting the data. In the bigger picture, the data collected will lead to conclusions and set bases for important decisions for similar projects in the future, enabling a lesson-learning approach to design new oil fields. The accumulated theoretical and practical research results of smart-field implementation require analysis and synthesis to maintain perspective of the entire project. Both were applied in the Mender field, which is the subject of the complete paper. Problem Statement The Mender parent field has been producing since 2013 with minimal digitalization for wellheads. Wells are not fit-ted with remote sensors, and operators have been visiting the wells to collect data using analog gauges. Collected data are stored in computers or as hard copies. Some critical data is lost, which affects decision-making. The new Mender field is 50 km from the parent field and is in a sensitive area close to international borders. The field area is a wildlife reserve for various endangered animals. The nature of operations is highly critical because of concentrations of hydrogen sulfide (H2S) that could jeopardize employees’ health and safety.

IMPACT OF GAS LIFT INJECTION RATE ON OIL PRODUCTION RATE

As worldwide energy demand continues to grow, oil and gas fields have spent hundreds of billions of dollars to build the substructures of smart fields. Management of smart fields requires integrating knowledge and methods in order to automatically and autonomously handle a great frequency of real-time information streams gathered from those wells. Furthermore, oil businesses movement towards enhancing everyday production skills to meet global energy demands signifies the importance of adapting to the latest smart tools that assist them in running their daily work.
 A laboratory experiment was carried out to evaluate gas lift wells performance under realistic operations in determining reservoir pressure, production operation point, injection gas pressure, port size, and the influence of injection pressure on well performance. Lab VIEW software was used to determine gas passage through the Smart Gas Lift valve (SGL) for the real-time data gathering. The results showed that the wellhead pressure has a large influence on the gas lift performance and showed that the utilized smart gas lift valve can be used to enhanced gas Lift performance by regulating gas injection from down hole.

A Deep-Learning-Based Smart Healthcare System for Patient’s Discomfort Detection at the Edge of Internet of Things

The Internet of Things (IoT) widely supports the smart healthcare field; combined with computer vision, machine, and deep learning techniques; it provides fast and accurate services for automated patient discomfort monitoring/detection systems. Traditional patient monitoring systems are commonly composed of wearable sensors and vision-based methods. In this article, an IoT-based noninvasive automated patient's discomfort monitoring/detection system is presented and implemented, using a deep-learning-based algorithm. The system is based on an IP camera device; the patient's body's movement and posture are detected without using any wearable devices. The Mask-RCNN method is employed for the extraction of different key points on the patient body. These detected key points are then transformed into six major body organs using association rules of data mining. Furthermore, for analyzing the patient's discomfort, detected key point coordinates information is measured. Finally, the distance and the temporal threshold are applied to classify movements as either associated with normal or discomfort conditions. These key points information is also used to determine the postures of the patient lying on the bed. The patient's body position and posture are continuously monitored, based on which comfort and discomfort level are discriminated. For experimental evaluation, different video sequences are recorded covering two patient's beds. The experimental results show the proposed system's worth by achieving a true-positive rate of 94% and a false-positive rate of 7%.

Determination of crop coefficient for chufa crop (Cyperus esculentus L. var. sativus Boeck.) for sustainable irrigation scheduling

Chufa is a traditional crop in L'Horta de València (Spain), a historical agricultural system that has been recognised in the register of Globally Important Agricultural Heritage Systems, managed by the Food and Agriculture Organization of the United Nations (FAO), and is one of the six protected Mediterranean and metropolitan horticultural fields as per the European Environment Agency. Chufa is a horticultural crop cultivated for its tubers. Our team has carried out different studies to improve the sustainability of chufa crop, particularly the efficiency of irrigation water use; however, the complete irrigation water requirements remain unknown. Therefore, the main aim of this study was to determine the crop coefficient values for chufa crop along its crop cycle using a smart field weighing lysimeter for three consecutive seasons and to determine its irrigation water requirements. The single crop coefficient values are 0.32, 1.40, and 0.80 for the initial stage, mid-season stage, and end of the late season stage, respectively for local conditions and 1.24 and 0.73 for mid- and late season stages, respectively for standard conditions. FAO segmented and second-order polynomial functions are presented to describe the crop coefficient evolution throughout the cycle, and could be used for irrigation scheduling and may lead to important water savings. The average seasonal net irrigation water requirement for chufa crop was approximately 640 mm, representing around 57% of the irrigation depth usually applied by chufa growers. The water savings that may be achieved by the adjustment of irrigation water with irrigation water requirements, using the crop coefficient, would improve, to a great extent, the sustainability of the L'Horta de València historical agricultural system, in view of the water scarcity resulting from climate change. This sustainable irrigation scheduling will improve the ecosystem indices, which have been altered by the application of over-irrigation, in the area.

Auto Gas Lift-The Intelligent Well Solution to Increase Productivity

As the global demand for energy keeps growing, the demand for oil and gas will keep mounting. Billions of dollars are being spent by oil and gas industries to set up the infrastructures of smart field. Managing these fields involves combined methods and knowledge for unmanned and independent handling of these field an enough number of synchronized data is gathered and monitored from wells for smooth and uninterrupted operation. Among all forms of artificial lift, the most common used is automatic gas lift, which is mostly used for offshore wells. The reason for its simplicity and relative use is its downhole flexibility, simplicity, reliability, and capability to operate over a widespread range of flow rates with restricted well head space. Implying the Automatic Gas lift (AGL) technique can cut the operational cost and increases the “Net Present Value” (NPV) by maximizing recovery from a field. In this study, GAP models were being made for DN horizontal, DI Vertical, Non-Contagious (NC), and AGL. The models made were used to predict cumulative oil production, gas production, water production, and pressure drop. After all the predictions were made comparative study was done in order to understand the trends. The results demonstrate substantial increase in oil recovery using Auto Gas Lift in the field through vertical wells 1,2 and 3 which otherwise is quite low in do-nothing case. Moreover, it has been observed that Auto Gas Lift provides higher recovery compared to vertical wells. Hence, fewer number of horizontal wells can be bored in the field to increase revenues and ultimate increase in efficiency of the reserves.

Light-Associated Surface Wrinkling-Based Metrology for the Photosoftening Characterization in Azobenzene-Polymer Supramolecular Complexes.

As an intriguing characteristic of azobenzene-containing materials (azo-materials), photoinduced changes in mechanical properties (e.g., photosoftening) have stimulated many efforts both theoretically and experimentally. Here a simple yet powerful tool (i.e., a light-associated surface wrinkling-based method) to study the photosoftening effect in azobenzene-polymer (azo-polymer) supramolecular complexes is reported. The photo-induced modulus decrease of supramolecular complex films is deduced by analyzing the change of critical wrinkle wavelength of strain-induced surface wrinkling, in the case of varying experiment parameters. In particular, thanks to the facile modular tunability of the supramolecular system, the photosoftening effect has been systematically investigated as a function of azo-moiety content and the molecular weight of the host polymer. Notably, a photosoftening coefficient that is related to the chemical composition/structure of azo-polymers is introduced, and a simple formula that can quantify the connection of the photosoftening with external irradiation conditions and internal chemical factors of azo-polymers is derived for the first time. The obtained results are of great importance not only to enhance understanding of the photosoftening mechanism, but also to thoroughly apply it in diverse smart fields.

The role of innovations in the development of agriculture in Russia

This article is intended to substantiate the role of innovations in the development of agriculture in Russia. The authors of the article focused on identifying the importance of innovative techniques and technologies in the modern development of the agricultural industry. The current directions of innovative developments in the agricultural sector in Russia have been identified and investigated. The conditions for achieving effective implementation of digital land use projects are presented; “Smart field”; “Smart garden; Smart farm. The experience and level of development of innovative techniques and technologies in foreign countries are considered. An up-to-date list of both Russian and foreign manufacturers of innovative developments, the buyers of which are domestic agricultural organizations, is presented. The factors that hinder the active implementation of innovations in the activities of agricultural entities in Russia have been identified. A diagram of the relationship between the components of the process of creating and applying innovative technologies has been developed. Also the author’s schematic position of the role and place of innovations in the process of creating and applying innovative technologies is presented. As a result of the research, there were given recommendations for eliminating the identified problems in the field of introducing innovative techniques and technologies in agricultural production.

RETRACTED: Visualization system of orthopedic personalized orthosis based on FPGA and sensor

The orthosis improves the function of enhancing the body's alignment, repair the damaged region, improve the prevention or deformation, protect the joint or limb, controlled restriction and pain relief, and provide feedback to the body power and the external device. Smart sensors can communicate with different digital network parameters and develop their applications in industrial, medical, and related fields. Plastic surgeons and orthosis must use intelligent sensors to control and monitor all patient parameters to improve and hope in life, accurate and reliable results. The sensors on the orthopedic devices, such as tools and equipment, are useful to report on the device's development and the patient's body. Smart sensors, monitors, blood pressure, anesthesia conveyor, sleep apnea machine, oxygen concentrator, temperature, kidney dialysis machines, and a fluid management system are used. Wireless smart sensors and Field Programmable Gate Array (FPGA) are orthopedic patients' data sent immediately within the orthopedic implant. And to reduce the risk of effective ways to improve patient care, potential applications of these sensors are to monitor the pressure for reducing the failure of the internal temperature and tissue necrosis and transplantation. The proposed sensor and FPGA proved to be successful in the orthopedic field for better care of patients.

Current state and prospects for the development of smart field technologies (general review)

Current state and prospects for the development of smart field technologies (general review)

Research and design of the smart field digital surgery system for emergency medical rescue

Natural disasters happened frequently around the world resulted in vast injured persons. The injured needs immediate on-site treatment to either save life or decrease mortality rate. The field surgery system, constructing a complete field on-site treatment force, is the fundamental to provide immediate medical care for the injured. In this paper, a smart field digital surgery system, integration with remote consultation system, medical information system and self-support system, was constructed to satisfy the demand of fast surgical treatment for emergency medical rescue in complex regional environment. The field digital surgical treatment technology platform for the injured in emergency was established based on taking the control of the cleanliness of the surgical cabin, designing a remote consultation system, developing the medical information system, as well as designing miniaturization magnet of field magnetic resonance imaging (MRI) system, which significantly improved the surgical treatment capability of the field digital surgery system.

Heuristic and Statistical Prediction Algorithms Survey for Smart Environments

There is a growing interest in the development of smart environments through predicting the behaviors of inhabitants of smart spaces in the recent past. Various smart services are deployed in modern smart cities to facilitate residents and city administration. Prediction algorithms are broadly used in the smart fields in order to well equip the smart services for the future demands. Hence, an accurate prediction technology plays a vital role in the smart services. In this paper, we take out an extensive survey of smart spaces such as smart homes, smart farms and smart cars and smart applications such as smart health and smart energy. Our extensive survey is based on more than 400 articles and the final list of research studies included in this survey consist of 134 research papers selected using Google Scholar database for period of 2008 to 2018. In this survey, we highlight the role of prediction algorithms in each sub-domain of smart Internet of Things (IoT) environments. We also discuss the main algorithms which play pivotal role in a particular IoT subfield and effectiveness of these algorithms. The conducted survey provides an efficient way to analyze and have a quick understanding of state of the art work in the targeted domain. To the best of our knowledge, this is the very first survey paper on main categories of prediction algorithms covering statistical, heuristic and hybrid approaches for smart environments.

A design methodology for matching smart health requirements

SummaryAs now well established, the world population is aging rapidly and, according to World Health Organization (WHO), the amount of people aged 60 years and older is expected to total 2 billion in 2050. For this reason, an emerging important issue is the definition of a new generation of healthcare platforms capable of monitoring people's quality of life. In this article, we propose a new methodology that supports the entire requirement elicitation process starting from the initial phase of gathering the requirements, both clinical, technological, and end‐user, up to the choice of the most suitable solution. Our proposal provides a new new iterative model in the smart healthcare field research area. Furthermore we apply our proposal in a real scenario and we report the end‐to‐end implementation of the proposed methodology.

Electrically conductive cotton fabric coatings developed by silica sol-gel precursors doped with surfactant-aided dispersion of vertically aligned carbon nanotubes fillers in organic solvent-free aqueous solution

HypothesisFrom the end of the twentieth century, the growing interest in a new generation of wearable electronics with attractive application for military, medical and smart textiles fields has led to a wide investigation of chemical finishes for the production of electronic textiles (e-textiles). ExperimentsHerein, a novel method to turn insulating cotton fabrics in electrically conductive by the deposition of three-dimensional hierarchical vertically aligned carbon nanotubes (VACNT) is proposed. Two VACNT samples with different length were synthesized and then dispersed in 4-dodecylbenzenesulfonic acid combined with silica-based sol-gel precursors. The dispersed VACNT were separately compounded with a polyurethane thickener to obtain homogeneous spreadable pastes, finally coated onto cotton surfaces by the “knife-over-roll” technique. FindingsShorter VACNT-based composite showed the best electrical conductivity, with a sheet resistance value less than 4.0 · 104 ± 6.7 · 103 Ω/sq. As demonstrated, developed e-textiles are suitable for application as humidity sensing materials in wearable smart textiles by exhibiting adequate response time for end-users and repeatability at several exposure cycles, still maintaining excellent flexibility. The proposed environmentally-friendly and cost-effective method can be easily widened to the scalable production of CNT-containing conductive flexible coatings, providing additional support to the development of real integration between electronics and textiles.

Building Continuous Time Crystals from Rare Events.

Symmetry-breaking dynamical phase transitions (DPTs) abound in the fluctuations of nonequilibrium systems. Here, we show that the spectral features of a particular class of DPTs exhibit the fingerprints of the recently discovered time-crystal phase of matter. Using Doob's transform as a tool, we provide a mechanism to build classical time-crystal generators from the rare event statistics of some driven diffusive systems. An analysis of the Doob's smart field in terms of the order parameter of the transition then leads to the time-crystal lattice gas (TCLG), a model of driven fluid subject to an external packing field, which presents a clear-cut steady-state phase transition to a time-crystalline phase characterized by a matter density wave, which breaks continuous time-translation symmetry and displays rigidity and long-range spatiotemporal order, as required for a time crystal. A hydrodynamic analysis of the TCLG transition uncovers striking similarities, but also key differences, with the Kuramoto synchronization transition. Possible experimental realizations of the TCLG in colloidal fluids are also discussed.