FPGA-based Fused Smart Sensor for Real-Time Plant-Transpiration Dynamic Estimation

Plant transpiration is considered one of the most important physiological functions because it constitutes the plants evolving adaptation to exchange moisture with a dry atmosphere which can dehydrate or eventually kill the plant. Due to the importance of transpiration, accurate measurement methods are required; therefore, a smart sensor that fuses five primary sensors is proposed which can measure air temperature, leaf temperature, air relative humidity, plant out relative humidity and ambient light. A field programmable gate array based unit is used to perform signal processing algorithms as average decimation and infinite impulse response filters to the primary sensor readings in order to reduce the signal noise and improve its quality. Once the primary sensor readings are filtered, transpiration dynamics such as: transpiration, stomatal conductance, leaf-air-temperature-difference and vapor pressure deficit are calculated in real time by the smart sensor. This permits the user to observe different primary and calculated measurements at the same time and the relationship between these which is very useful in precision agriculture in the detection of abnormal conditions. Finally, transpiration related stress conditions can be detected in real time because of the use of online processing and embedded communications capabilities

Agricultural Management through Wireless Sensors and Internet of Things

Agriculture plays a significant role in most countries and there is an enoromous need for this industry to become “Smart”. The Industry is now moving towards agricultural modernization by using modern smart technologies to find solutions for effective utilization of scarce resources there by meeting the ever increasing consumtion needs of global population. With the advent of Internet of Things and Digital transformation of rural areas, these technologies can be leveraged to remotely monitor soil moisture, crop growth and take preventive measures to detect crop damages and threats. Utilize artificial intelligence based analytics to quickly analyze operational data combined with 3rd party information, such as weather services, expert advises etc., to provide new insights and improved decision making there by enabling farmers to perform “Smart Agriculture”. Remote management of agricultural activities and their automation using new technologies is the area of focus for this research activity. A solar powered remote management and automation system for agricultural activities through wireless sensors and Internet of Things comprising, a hardware platform based on Raspberry Pi Micro controller configured to connect with a user device and accessed through the internet network. The data collection unit comprises a set of wireless sensors for sensing agricultural activities and collecting data related to agricultural parameters; the base station unit comprising: a data logger; a server; and a software application for processing, collecting, and sending the data to the user device. The user device ex: mobile, tablet etc. can be connected to an internet network, whereby an application platform (mobile-app) installed in the user device facilitates in displaying a list of wireless sensor collected data using Internet of Things and a set of power buttons. This paper is a study and proposal paper which discusses the factors and studies that lead towards this patent pending invention, AGRIPI

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering

Air Force Institute of Technology Research Report 2009

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

Laser absorption spectroscopic tomography with a customised spatial resolution for combustion diagnosis

Combustion is a widely used energy conversion technology. However, post-combustion gas emissions have adverse effects on climate change. To address the urgent need for carbon neutrality, efforts are being made to develop cleaner fuels and improve combustion efficiency. Accurate in situ measurements of temperature and species concentration are crucial for analysing and diagnosing the combustion process. In industrial applications, probed-based measurement methods are commonly used to detect temperature and species concentration in the combustion, favoured by their simplicity. However, the probe-based techniques are limited in their spatial resolution, as only point-wise measurements can be provided by them. Additionally, their principle often restricts their temporal resolution, which limits their ability to capture the dynamics of the combustion process. To overcome these limitations, researchers are actively working on developing rapid and multi-dimensional in situ techniques for temperature and species concentration monitoring. Laser Absorption Spectroscopy (LAS) has gained significant attention for its non-intrusive nature and fast response in combustion diagnostics. LAS techniques use an emitter-receiver configuration to measure the line-of-sight light intensity absorbed by species in the gaseous medium. By collecting multiple line-of-sight measurements from different angles, LAS enables tomographic measurement of the combustion process. However, implementations of LAS tomography face challenges due to the physical dimensions of the emitter and receiver and the optical access to industrial combustors. These limitations lead to incomplete measurements, which are key factors of ill-posed problems and artefacts in the reconstructed images. The artefacts lead to inaccuracy and unreliability of the diagnostic results. Increasing physical sampling density is one of the most straightforward ways to alleviate the ill-posed problem caused by inadequate line-of-sight measurements. Improvements in sensors have been demonstrated in previous research, such as optimising laser beam arrangement and reducing the spacing of neighbouring laser beams. In this work, a novel design of a miniature and modular sensor is firstly introduced. It reduces the beam spacing between adjacent laser beams, allowing for a more precise and detailed reconstruction of temperature and species concentration distributions. Meanwhile, modular design allows for customisation and adaptation to various measurement requirements. This flexibility in deployment reduces the cost of the LAS technique. The application of small beam spacing in characterising the non-uniformity of the combustion process has also been demonstrated in this thesis. A multi-channel LAS sensor is developed and applied to exhaust measurements of a commercial auxiliary power unit. The results show that the small beam spacing allows a detailed understanding of the exhaust plume at the mixing zone between the exhaust gas and surrounding air. This spatial information can be used to improve the accuracy of temperature and species concentration measurements. On the other hand, prior knowledge, such as smoothness and sparsity of the measurement target and beam arrangement of the LAS tomographic sensor is used to provide extra physical information to the ill-posed inverse problem. To incorporate the beam arrangement information into the reconstruction process, a new meshing scheme is proposed in this thesis. The scheme dynamically allocates smaller meshes in the beam-dense regions and coarser meshes in the beam-loose regions. This adaptive meshing scheme ensures a finer resolution in detailing the combustion zone where the beams are closely spaced while maintaining the integrity of the physical model by using less resolved reconstruction in the bypass flows or regions where the beams are further apart. As a result, the proposed meshing scheme improves the reconstruction accuracy of the combustion zone. Overall, this PhD project designed and developed LAS tomographic sensors and methods that enable accurate and fast measurement of gas temperature and species concentration in combustion processes with a customised spatial resolution. The main contributions of this thesis include the design and prototyping of a miniature and modular optical sensor for flexible LAS tomography; the development of a multi-channel LAS sensor for simultaneously monitoring exhaust gas temperature and water vapour concentration in gas turbine engines; and the development of a size-adaptive hybrid meshing scheme to improve the reconstruction of target flow fields

WOFEX 2021 : 19th annual workshop, Ostrava, 1th September 2021 : proceedings of papers

The workshop WOFEX 2021 (PhD workshop of Faculty of Electrical Engineer-ing and Computer Science) was held on September 1st September 2021 at the VSB – Technical University of Ostrava. The workshop offers an opportunity for students to meet and share their research experiences, to discover commonalities in research and studentship, and to foster a collaborative environment for joint problem solving. PhD students are encouraged to attend in order to ensure a broad, unconfined discussion. In that view, this workshop is intended for students and researchers of this faculty offering opportunities to meet new colleagues.Ostrav

NASA Tech Briefs, September 1993

Topics include: Microelectronics; Electronic Components and Circuits; Electronic Systems; Physical Sciences; Materials; Computer Programs; Mechanics; Machinery/Automation; Manufacturing/Fabrication; Mathematics and Information Sciences; Life Sciences; Books and Reports

Early growth technology analysis : case studies in solar energy and geothermal energy

Thesis (S.M. in Technology and Policy)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 85-87).Public and private organizations try to forecast the future of technological developments and allocate funds accordingly. Based on our interviews with experts from MIT's Entrepreneurship Center, Sloan School of Management, and IBM, and review of literature, we found out that this important fund allocation process is dominated by reliance on expert opinions, which has important drawbacks alongside its advantages. In this Thesis, we introduce a data-driven approach, called early growth technology analysis, to technology forecasting that utilizes diverse information sources to analyze the evolution of promising new technologies. Our approach is based on bibliometric analysis, consisting of three key steps: extraction of related keywords from online publication databases, determining the occurrence frequencies of these keywords, and identifying those exhibiting rapid growth. Our proposal goes beyond the theoretical level, and is embodied in software that collects the required inputs from the user through a visual interface, extracts data from web sites on the fly, performs an analysis on the collected data, and displays the results. Compared to earlier software within our group, the new interface offers a much improved user experience in performing the analysis. Although these methods are applicable to any domain of study, this Thesis presents results from case studies on the fields of solar and geothermal energy. We identified emerging technologies in these specific fields to test the viability of our results. We believe that data-driven approaches, such as the one proposed in this Thesis, will increasingly be used by policy makers to complement, verify, and validate expert opinions in mapping practical goals into basic/applied research areas and coming up with technology investment decisions.by Ayse Kaya Firat.S.M.in Technology and Polic

Applications of Mathematical Models in Engineering

The most influential research topic in the twenty-first century seems to be mathematics, as it generates innovation in a wide range of research fields. It supports all engineering fields, but also areas such as medicine, healthcare, business, etc. Therefore, the intention of this Special Issue is to deal with mathematical works related to engineering and multidisciplinary problems. Modern developments in theoretical and applied science have widely depended our knowledge of the derivatives and integrals of the fractional order appearing in engineering practices. Therefore, one goal of this Special Issue is to focus on recent achievements and future challenges in the theory and applications of fractional calculus in engineering sciences. The special issue included some original research articles that address significant issues and contribute towards the development of new concepts, methodologies, applications, trends and knowledge in mathematics. Potential topics include, but are not limited to, the following: Fractional mathematical models; Computational methods for the fractional PDEs in engineering; New mathematical approaches, innovations and challenges in biotechnologies and biomedicine; Applied mathematics; Engineering research based on advanced mathematical tools