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This new book provides an insightful look at the varied and
exciting uses and applications of Wi-Fi and the Internet of Things
in agriculture. With internet-enabled communications becoming more
widely available, farms and agricultural establishments can take
advantage of these new technologies for a wide range of farm
operations, such as crop management, farm vehicle tracking,
livestock monitoring, storage monitoring, and more. The collected
data from these devices can be stored in the cloud system or server
and accessed by the farmers via the internet or mobile phones. This
book shows the many benefits to farmers from applying IoT,
including better utilizing information for monitoring crops,
optimizing water use, planning effective fertilization strategies,
and saving time and reducing the operation expenses. Topics include
using IoT for vertical farming, IoT-based smart irrigation system,
landslide susceptibility assessment, automated aeroponics systems,
crop survival analysis, and more. The volume also considers the
challenges of IoT in agriculture, such as the requirements of
applications of wireless sensor networks, the threat of attacks and
the detection of vulnerabilities in wireless sensor networks, and
more. Internet of Things for Agriculture 4.0: Impact and Challenges
provides a better understanding of the time- and resourcing-saving
benefits of wireless sensors and remote monitoring devices in
agriculture. The volume will be useful for those involved in
agricultural operations as well as scientists and researchers, and
faculty and students in agriculture and computer and information
science engineering.
This book provides a better understanding of Fuzzy set theory,
Fuzzy logic and Neural Networks and various other techniques seem
very well suited for modelling and controlling a real system.
Energy is of major importance to civilisation, because it is
driving force which binds human race. The estimation of energy in
the form of renewable and sustainable is one of the important
aspects to understand the how resources are harnessed and to
predict what might happen under various possible future conditions.
Using available modelling techniques to generate the best
algorithms, the objective is to determine the best solution in
terms of comparing the performances of the solutions through
different parameters for a specific case. Consumption of Fossil
fuels at a rapid pace has generated an alarming situation and with
the subsequent increase in the number of vehicle the pollution
level has reached well beyond human's control. This is frightening
enough to observe the fact that the pollution level has surpassed
all records and the need of the hour is to find an alternate fuel
which can really be of great assistance in reducing the exhaust
emission and augment the performance parameters of engine. Major
researches are carried out on various engines to draw closer
towards a realistic solution. Experiments performed on various
engines are considered to be time consuming and the expenses met to
perform these experiments are too costly, so the need of soft
computing techniques involved in this area. Soft computing can be
better described as the process to find the solution to an inexact
problem. Soft computing has showed lot of potential in giving the
researchers the exact solution may be in case of validating or
predicting the performance and emission parameters. Artificial
Neural Network (ANN), Adaptive Neuro Fuzzy Inference system
(ANFIS), Fuzzy Expert System (FES), Response Surface Methodology
(RSM) and Support Vector Machine (SVM) are the various soft
computing techniques widely used. This book focuses on to carry out
the comprehensive review and various other experimental works of
various researchers who have carried out the work on these various
soft computing techniques on various engines with various
alternative fuels on the basis of modelling techniques, time is
saved to a great extent and the capital investment involved is
comparably very low. Various modelling techniques are being readily
used to predict the performance parameters for various engines and
modelling techniques have become the readily available tool to
compare and validate the experimental work being carried out by
researchers to get accurate matching with the experimental data.
The benefit of this issue will be at large in connecting with
varieties of work done in the field of Biomass which includes wood
and wood waste, municipal solid waste. Landfill gas and biogas.
Ethanol, Biodiesel, Hydropower, Geothermal, Wind, Solar. Thus soft
computing techniques are fast and reliable hence, they can be a
substitute for conventional experiments.
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