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Intelligent Manufacturing Components, Challenges, and Opportunities
Intelligent Manufacturing shows transformative paradigms in the manufacturing industry; leveraging advanced technologies such as Artificial Intelligence (AI), Internet of Things (IoT), and robotics, to develop highly automated and adaptive production systems. This chapter outlines the Intelligent Manufacturing process, including its key principles, components, challenges, and opportunities. The combination of Machine Learning (ML) techniques and AI enables decision-making, real-time optimisation, and predictive analytics of manufacturing processes, productivity, and quality of products. Robotics and IoT devices play critical roles in enabling automation, data collection, and connectivity within Intelligent Manufacturing environments. Additionally, Digital Twin technology facilitates virtual simulation, modelling, and optimisation of production systems. While Intelligent Manufacturing offers significant benefits, it also presents challenges viz. high investments, integration complexity, and workforce reskilling requirements. Overcoming the challenges requires a holistic approach involving collaboration between industry stakeholders, government agencies, academia, and technology providers. Overall, Intelligent Manufacturing represents a promising future for the manufacturing industry, offering opportunities for innovation, competitiveness, and sustainable growth in a rapidly evolving global economy. 2025 selection and editorial matter, Alka Chaudhary, Vandana Sharma, and Ahmed Alkhayyat individual chapters, the contributors. -
Taxonomic revision and molecular phylogeny of flemingia subgenus rhynchosioides (Leguminosae)
A taxonomic revision of Flemingia subg. Rhynchosioides based on morphology and molecular information (matK and ITS) is presented. The subgenus comprises six herbaceous taxa (F. gracilis, F. mukerjeeana, F. nilgheriensis, F. rollae, F. tuberosa and F. vestita). All species except F. vestita are endemic to India. Morphological evidence and molecular phylogeny revealed that the subgenus is monophyletic. Nevertheless, the systematic position of F. tuberosa remains unclear on account of its unique ecology and inflorescence. A new species, F. mukerjeeana, is described and four binomials, namely F. gracilis, F. nilgheriensis, F. tuberosa and F. vestita have been lectotypified. Furthermore, all species have been described, illustrated and their ecology discussed. A taxonomic key including the recently described species from Thailand, F. sirindhorniae, is also provided for easy identification. 2019 Naturalis Biodiversity Center. -
Defluoridation of Drinking WaterFluoride Wars
Fluorine is also known as two-edged sword. At lower doses, it influences tooth by inhibiting tooth caries, while in high doses, it causes dental and skeletal fluorosis. It is known that some quantity of fluoride is important for the formation of tooth enamel and mineralization in tissues. The present work aims at providing safe and potable water to rural areas where this element has created a menace. This work also suggests the use of few adsorbents such as paddy husk and coir pith which are affordable and removes fluorine to greater extent. The study concludes that materials which are used as adsorbents and can be safely inculcated as fluorine removal adsorbents which help people to have safe potable water. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Removal of Struvite in Wastewater Using Anammox Bacteria
Struvite precipitation in wastewater has proved to be an effective method in treating wastewater and has helped in the recovery of ammonia nitrogen and phosphate phosphorus. Nutrient recovery from wastewater has become a new trend attracting the interests of several researchers. Extraction of the nutrients based on struvite crystals as nutrition sources from wastewater has been acknowledged as a need of the hour solution to tackle the water pollution issue. This review focuses on the featured characteristics of struvite as a chemical fertilizer for plant and the struvite formation process related to physiochemical conditions in wastewaters. In the present work, struvite precipitation in the actual swine wastewater is studied by strategically controlling aeration, pH, and mixing of anammox bacteria. The effect of organic solids in the wastewater has also been studied. Laboratory experiments were conducted by optimizing pH value. pH was found to be an important parameter in the simultaneous removals of ammonium nitrogen and orthophosphate. This work reveals that the struvite removal from wastewater can be reduced to 80% using anammox bacteria. Springer Nature Singapore Pte Ltd. 2022. -
Degradation of azodyes in wastewater by using hydrodynamic cavitation technique
The organic waste water discharged from various industries consists of large amounts of dyes & cyanides & other toxic carcinogenic pollutants which are harmful to human health & ecosystem. Release of carcinogenic dyes is hazardous & has a detrimental effect on the well being of an individual. The present work is focussed at finding the viability of hydrodynamic cavitations process in the degradation of dyes. To study the degradation, influence of various parameters on degradation rate has been studied. BEIESP. -
Origami foldaway support for beginners using image processing
Various origami works are distributed as origami books in which a succession of collapsing operations with basic outlines is portrayed. In any case, the origami book reader often will give up the instruction of the book middle, because it is too difficult to understand a way to fold in accordance with the diagrams. This paper proposes an approach to find the next step how to do the folding operation, especially for origami beginners. First, a method of detecting the folding operation based on camera images is been detected by canny edge detection. Then, in order to get the next operation camera image is been compare with the database images with the help of Bag of a visual word and Speed up robust features(SURF) detector to detect the key points by finding out the nearest neighboring distance ration (NNDR) measures to find out the similarities. 2016 Authors. -
Rayleigh-Bard convection in mono and hybrid nanoliquids in an inclined slot
Linear stability analysis is conducted to investigate the longitudinal and transverse rolls (TRs) generated in Rayleigh-Bard convection in mono and hybrid nanoliquids confined between two infinite inclined parallel slots. Thermophysical properties of six mono nanoliquids and fifteen hybrid nanoliquids are calculated for different volume fractions (0.5%, 1%, 2%) using phenomenological laws and mixture theory. The shooting method is used to solve boundary eigenvalue problems to obtain the eigenvalues for 16 different boundary conditions. It is observed that as the inclination angle is increased, it delays the onset of longitudinal rolls in the case of all boundary conditions. However, it advances the onset of TRs except when the lower plate is adiabatic. The addition of mono and hybrid nanoparticles results in the advancement of the onset of convection. The addition of SWCNT and SWCNT Al 2 O 3 accelerates the onset of convection the most while Cu and Cu-Ag accelerates the onset of convection the least amongst the mono and hybrid nanoparticles considered in the study. 2023 IOP Publishing Ltd. -
Analysis and Prediction of Suitable Model for Coconut Production Estimates in South Indian States
The study attempts to forecast coconut production in major coconut-producing states in India. The future projections on coconut production have been calculated based on yearly data for 73 years (194950 to 202122) accessed from the database of Indiastat (2022). We have used prominent forecasting techniques for the purpose and a suitable model has been chosen based on the lowest results of MAPE. The damped linear trend has been chosen for forecasting coconut production in Karnataka whereas Differenced first-order Auto Regressive model with drift has been adopted for Kerala and Karnataka. This study has considered a large dataset compared to other existing works and has chosen states that produce coconut on a large scale in India. Along with this, this study also attempts to find which state will produce more nuts for the Indian coconut industry, which can help the concerned stakeholders to take necessary decisions. Future projections depict that Kerala will continue to be the largest producer of coconut and Karnataka will show remarkable performance in coconut production during the upcoming four years post-study period. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Machine learning approaches towards medical images
Clinical imaging relies heavily on the current medical services' framework to perform painless demonstrative therapy. It entails creating usable and instructive models of the human body's internal organs and structural systems for use in clinical evaluation. Its various varieties include signal-based techniques such as conventional X-ray, computed tomography (CT), magnetic resonance imaging (MRI), ultrasound (US) imaging, and mammography. Despite these clinical imaging techniques, clinical images are increasingly employed to identify various problems, particularly those that are upsetting the skin. Imaging and processing are the two distinct patterns of clinical imaging. To diagnose diseases, automatic segmentation using deep learning techniques in the field of clinical imaging is becoming vital for identifying evidence and measuring examples in clinical images. The fundamentals of deep learning techniques are discussed in this chapter along with an overview of successful implementations. 2023, IGI Global. All rights reserved. -
Empowering Renewable Energy Using Internet of Things
The massive communication of information over network gadgets associated with the internet trades data starting from one to another with no sort of human cooperation. As innovation is advancing, interconnected organizations give data to each other to impart. The energy utilization is happening at an extremely quick rate, debilitating the assets in delivering it at a similar rate, and the entirety of this requires a transformation to save energy. Information is the focal point of the Internet of Things (IoT), and it has all the information to which there was no entrance before; this information can be utilized in the revolution of the energy management framework. By utilizing advanced IoT innovations, the embracement of renewable can be upgraded signifcantly further. The reconciliation of IoT in renewable energy is empowering its development by and large. The Author(s), under exclusive license to Springer Nature Switzerland AG 2023. -
FISCAL DECENTRALIZATION IN INDIA AND CHINA: Experiences in service delivery
[No abstract available] -
Identifying a Range of Important Issues to Improve Crop Production
Crop yield production value update has a beneficial practical impact on directing agricultural production and informing farmers of changes in crop market prices. The main objective of the suggested method is to put the crop selection technique into practise so that it may be used to address a variety of issues facing farmers and the agricultural industry. As a result, the yield rate of crop production is maximised, which benefits our Indian economy. land conditions of several kinds. So, using a ranking system, the quality of the crops are determined. This procedure also alerts farmers to the rate of crops of low and high quality. Due to the use of multiple classifiers, using an ensemble of classifiers paves the way for better prediction decisions. The decision-making process for selecting the output of the classifiers also incorporates a rating system. The price of a crop that will produce more is predicted using this method. 2023 IEEE. -
A Novel Assessment of Healthcare Waste Disposal Methods: Intuitionistic Hesitant Fuzzy MULTIMOORA Decision Making Approach
Waste produced from medical facilities systems incorporates a blend of dangerous waste which can posture dangers to humans and ecological receptors. Lacking administration of healthcare waste can prompt hazard to medicinal service specialists, patients, public health, communities and the wider environment. Hence, proper management of healthcare waste is imperative to reduce the associated health and environment risk. In this paper, we extend the MULTIMOORA decision making method with intuitionistic hesitant fuzzy set to evaluate the healthcare waste treatment methods. Intuitionistic hesitant fuzzy set is a generalized form of a hesitant fuzzy set. Intuitionistic hesitant fuzzy set considers the uncertainty of data in a single framework and take more information into account. The MULTIMOORA method consists of three parts namely the ratio system, reference point approach and the full multiplicative form. In the optimal ranking methods, the IHF-MULTIMOORA method is uncomplicated it is able to be used practically with high dimension intuitionistic hesitant fuzzy sets. For pathological, pharmaceutical, sharp, solid and chemical wastes, the preferred waste disposal methods are deep burial, incineration, autoclave, deep burial, and chemical disinfection, respectively. 2013 IEEE. -
The hesitant Pythagorean fuzzy ELECTRE III: An adaptable recycling method for plastic materials
In this research article, introduce a novel decision making method called HPF-ELECTRE method by extending the ELECTRE III (ELimination and Choice Expressing REality) method with HPF (Hesitant Pythagorean Fuzzy) set. The efficiency of the new method is testing in the plastic recycling problem. One of the most hazardous domestic materials is plastic. The low biodegradability nature of plastic is a serious threat to the environment and to human life. Plastic is a synthetic chemical that do not belong to the natural world. Owing to the non-biodegradability, the only way to deal with this modern-world problem is recycling. Finding a suitable recycling method for disposing and recycling plastic materials is a major research issue. Propose the HPF-ELECTRE III method to find out the adaptable recycling method for plastics materials. The outranking in HPF-ELECTRE III method expand on concordance and discordance acceptability value values. Established method is an effective tool for decision making problems. 2020 Elsevier Ltd -
Smart Online Oxygen Supply Management though Internet of Things (IoT)
We are surrounded by oxygen in the air we We cannot even exist without the ability to breathe. The need for oxygen has increased during the COVID19 pandemic, and although there is enough oxygen in our country, the main issue is getting it to hospitals or those in need on time. This is simply due to a significant communication gap between suppliers and hospitals, so we plan to implement an idea that will close this gap using real-time tracking as we can track the movement of oxygen tankers by gathering the requirements. We are using an ESP32 Wi-Fi module, a MEMS pressure sensor that enables the combination of precise sensors, potential processing, and wireless communication, such as Wi-Fi, Bluetooth, IFTTT, and MQTT protocols, to implement it successfully. The pressure sensor publishes the value of oxygen remaining from the location to the MQTT broker. 2022 IEEE. -
A Precise Computational Method for Hippocampus Segmentation from MRI of Brain to Assist Physicians in the Diagnosis of Alzheimer's Disease
Hippocampus segmentation on magnetic resonance imaging is more significant for diagnosis, treatment and analyzing of neuropsychiatric disorders. Automatic segmentation is an active research field. Previous state-of-the-art hippocampus segmentation methods train their methods on healthy or Alzheimer's disease patients from public datasets. It arises the question whether these methods are capable for recognizing the hippocampus in a different domain. Therefore, this study proposes a precise computational method for hippocampus segmentation from MRI of brain to assist physicians in the diagnosis of Alzheimer's disease (HCS-MRI-DAD-LBP). Initially, the input images are pre-processed by Trimmed mean filter for image quality enhancement. Then the pre-processed images are given to ROI detection, ROI detection utilizes Weber's law which determines the luminance factor of the image. In the region extraction process, Chan-Vese active contour model (ACM) and level sets are used (UACM). Finally, local binary pattern (LBP) is utilized to remove the erroneous pixel that maximizes the segmentation accuracy. The proposed model is implemented in MATLAB, and its performance is analyzed with performance metrics, like precision, recall, mean, variance, standard deviation and disc similarity coefficient. The proposed HCS-MRI-DAD-LBP method attains in OASIS dataset provides high disc similarity coefficient of 12.64%, 10.11% and 1.03% compared with the existing methods, like HCS-DAS-MLT, HCS-DAS-RNN and HCS-DAS-GMM and in ADNI dataset provides high precision of 20%, 9.09% and 1.05% compared with existing methods like HCS-MRI-DAD-CNN-ADNI, HCS-MRI-DAD-MCNN-ADNI and HCS-MRI-DAD-CNN-RNN-ADNI, respectively. 2022 World Scientific Publishing Europe Ltd. -
IoT innovation in COVID-19 crisis
The COVID-19 pandemic is a current global threat that surpasses provincial and radical boundaries. Due to the onset of the pandemic disease, the whole world turned entirely in a couple of weeks. Its consequences have come across the personal and professional life of human beings. The current situation focuses on precautions such as wearing a mask, maintaining social distancing, and sanitizing hands regularly. An innovative platform, and smart and effective IoT technology may be applied to follow these steps. This platform fulfills all critical challenges at the time of lockdown situations. IoT technology is more helpful in capturing real-time patient data and other essential information. IoT allows the tracing of infected people and suspicious cases and helps diagnose and treat patients remotely. It also paves the way to deliver essential medical devices and medicines to quarantined places. In the present ongoing crisis, IoT technology is inevitable in monitoring patients infected with COVID-19 through sensors and intertwined networks. The consultations are given to the patients digitally through video conferencing without meeting the medical expert in person. After the diagnosis is made digitally, IoT devices are used to track health data. Smart thermometers are used instead of traditional ones to collect valuable health data and share it with experts. The IoT robots are now a proven technology used for cleaning hospitals, disinfecting medical devices, and delivering medicines, thus giving more time to healthcare workers to treat patients. 2023 Bentham Science Publishers. All rights reserved. -
Impact of Risk Perception on Use and Satisfaction with Online Pharmacies and Proposed Use of IoT to Minimize Risks
This study investigates consumer risk perceptions regarding online pharmacies and their impact on usage frequency and satisfaction. The growing popularity of online pharmacies offers benefits such as accessibility, cost savings, and privacy. However, significant risks, including the potential for counterfeit drugs and insufficient medical oversight, raise concerns. This study has measured consumer perceptions of risk, satisfaction, and usage frequency through a survey conducted in Northeast India, excluding Sikkim (online) and Sikkim (offline). The findings reveal that the fear of receiving counterfeit medications is a significant risk factor, negatively influencing both the frequency of use and consumer satisfaction. Despite this, the impact is relatively weak, suggesting that while risk perception is a concern, it does not significantly deter online pharmacy usage. The study suggests that integrating advanced technologies such as IoT, RFID, and blockchain can mitigate these risks by ensuring the authenticity of medications in the supply chain. 2024 IEEE. -
Inter-relational dynamics of factors affecting the emergence of orphan drugs; [Dynamique interrelationnelle des facteurs influennt lergence des micaments orphelins]
Orphan drugs are medications that are produced for the treatment of rare diseases. As there is less number of patients, the drug manufacturing companies are not keen in producing these drugs. Due to high costs of research and development and low profitability, companies do not want to invest in manufacturing of orphan drugs. Several laws have been passed by Governments of different nations to encourage the development of orphan drugs and make it available to patients. This study explores the interrelation dynamics of factors that has resulted in the greater availability of orphan drugs in recent times. Ten factors: internet technology, legislation, online patient support groups, government subsidiary, biotechnological advancements, corporate social responsibility, awareness and diagnosis of rare diseases and exclusive budgeting by pharmaceutical industries for orphan drugs related research and development and production were taken for the study. With a sample size of 38 experts, the technique of decision-making trial and evaluation laboratory (DEMATEL) was used for the study. It was found that information technology, legislation, support groups, and budget were the causes and the factors awareness, diagnosis, medicine availability, subsidiary, CSR and biotechnology emerged to be the effect. 2024 Acadie Nationale de Pharmacie -
