Search results for: smart and intelligent packaging

Authors: Jaqueline Nichi, Leila Da Costa Ferreira, Fabiana Barbi Seleguim, Gabriela Marques Di Giulio, Mariana Barbieri

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The transport sector is responsible for approximately 55% of global greenhouse gas (GHG) emissions, in addition to pollution and other negative externalities, such as road accidents and congestion, that impact the routine of those who live in large cities. The objective of this article is to discuss the application and use of distinct mobility technologies such as climate adaptation and mitigation measures in the context of smart cities in the Global South. The documentary analysis is associated with 22 semi structured interviews with managers who work with mobility technologies in the public and private sectors and in civil society organizations to explore solutions in multilevel governance for smart and low-carbon mobility based on the case study from the city of São Paulo, Brazil. The hypothesis that innovation and technology to mitigate and adapt to climate impacts are not yet sufficient to make mobility more sustainable has been confirmed. The results indicate four relevant aspects for advancing a climate agenda in smart cities: integrated planning, coproduction of knowledge, experiments in governance, and new means of financing to guarantee the sustainable sociotechnical transition of the sector.

Keywords: urban mobility, climate change, smart cities, multilevel governance

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Authors: L. Kanoksak, N. Sukanya, L. Napatsorn, T. Siriporn

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A growing population and demand for packaging are driving up the usage of natural resources as raw materials in the pulp and paper industry. Long-term effects of environmental is disrupting people's way of life all across the planet. Finding pulp sources to replace wood pulp is therefore necessary. To produce wood pulp, various other potential plants or plant parts can be employed as substitute raw materials. For example, pulp and paper were made from agricultural residue that mainly included pulp can be used in place of wood. In this study, cocoa pod husks were an agricultural residue of the cocoa and chocolate industries. To develop composite materials to replace wood pulp in packaging materials. The paper was coated with polybutylene adipate-co-terephthalate (PBAT). By selecting and cleaning fresh cocoa pod husks, the size was reduced. And the cocoa pod husks were dried. The morphology and elemental composition of cocoa pod husks were studied. To evaluate the mechanical and physical properties, dried cocoa husks were extracted using the soda-pulping process. After selecting the best formulations, paper with a PBAT bioplastic coating was produced on a paper-forming machine Physical and mechanical properties were studied. By using the Field Emission Scanning Electron Microscope/Energy Dispersive X-Ray Spectrometer (FESEM/EDS) technique, the structure of dried cocoa pod husks showed the main components of cocoa pod husks. The appearance of porous has not been found. The fibers were firmly bound for use as a raw material for pulp manufacturing. Dry cocoa pod husks contain the major elements carbon (C) and oxygen (O). Magnesium (Mg), potassium (K), and calcium (Ca) were minor elements that were found in very small levels. After that cocoa pod husks were removed from the soda-pulping process. It found that the SAQ5 formula produced pulp yield, moisture content, and water drainage. To achieve the basis weight by TAPPI T205 sp-02 standard, cocoa pod husk pulp and modified starch were mixed. The paper was coated with bioplastic PBAT. It was produced using bioplastic resin from the blown film extrusion technique. It showed the contact angle, dispersion component and polar component. It is an effective hydrophobic material for rigid packaging applications.

Keywords: cocoa pod husks, agricultural residue, composite material, rigid packaging

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Authors: Henni Sid Ahmed, Belbachir Mohamed Faouzi, Jean Caelen

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Behavior recognition has been studied for realizing drivers assisting system and automated navigation and is an important studied field in the intelligent Building. In this paper, a recognition method of behavior recognition separated from a real image was studied. Images were divided into several categories according to the actual weather, distance and angle of view etc. SIFT was firstly used to detect key points and describe them because the SIFT (Scale Invariant Feature Transform) features were invariant to image scale and rotation and were robust to changes in the viewpoint and illumination. My goal is to develop a robust and reliable system which is composed of two fixed cameras in every room of intelligent building which are connected to a computer for acquisition of video sequences, with a program using these video sequences as inputs, we use SIFT represented different images of video sequences, and SVM (support vector machine) Lights as a programming tool for classification of images in order to classify people’s behaviors in the intelligent building in order to give maximum comfort with optimized energy consumption.

Keywords: video analysis, people behavior, intelligent building, classification

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Authors: Sónia Ribeiro, Diana Farinha, Elsa Pereira, Hélia Sales, Filipa Figueiredo, Rita Pontes, João Nunes

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Conventional plastic impacts on Planet, natural resources contamination, human health as well as animals are the most attractive environmental and health attention. The lack of treatment in the end-of-life (EOL) phase and uncontrolled discard allows plastic to be found everywhere in the world. Food waste is increasing significantly, with a final destination to landfills. To face these difficulties, new packaging solutions are needed with the objective of prolonging the shelf-life of products as well as equipment solutions for the development of the mentioned packaging. FLUI project thus presents relevance and innovation to reach a new level of knowledge and industrial development focused in Ecodesign. Industrial equipment field for the manufacture of new packaging solutions based on biodegradable plastics films to apply in the food sector. With lesser environmental impacts and new solutions that make it possible to prevent food waste, reduce the production e consequent poor disposal of plastic of fossil origin. It will be a paradigm shift at different levels, from industry to waste treatment stations, passing through commercial agents and consumers. It can be achieved through the life cycle assessment (LCA) and ecodesign of the products, which integrates the environmental concerns in the design of the product as well as through the entire life cycle. The FLUI project aims to build a piece of new bio-PLA extrusion equipment with the incorporation of bioactive extracts through the production of flexible mono- and multi-layer functional films (FLUI systems). The biofunctional and biodegradable films will prompt the extension of packaged products’ shelf-life, reduce food waste and contribute to reducing the consumption of non-degradable fossil plastics, as well as the use of raw material from renewable sources.

Keywords: food packing, bioplastics, ecodesign, circular economy

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Authors: Mohsen Noroozi, Maryam Khalili

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Creating cities, objects and spaces that are economically, environmentally and socially sustainable and which meet the challenge of social interaction and generation change will be one of the biggest tasks of designers. Social sustainability is about how individuals, communities and societies live with each other and set out to achieve the objectives of development model which they have chosen for themselves. Urban lightning as one of the most important elements of urban furniture that people constantly interact with it in public spaces; can be a significant object for designers. Using intelligence by internet of things for urban lighting makes it more interactive in public environments. It can encourage individuals to carry out appropriate behaviors and provides them the social awareness through new interactions. The greatest strength of this technology is its strong impact on many aspects of everyday life and users' behaviors. The analytical phase of the research is based on a multiple method survey strategy. Smart lighting proposed in this paper is an urban lighting designed on results obtained from a collective point of view about the social sustainability. In this paper, referring to behavioral design methods, the social behaviors of the people has been studied. Data show that people demands for a deeper experience of social participation, safety perception and energy saving with the meaningful use of interactive and colourful lighting effects. By using intelligent technology, some suggestions are provided in the field of future lighting to consider the new forms of social sustainability.

Keywords: behavior pattern, internet of things, social sustainability, urban lighting

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Authors: Christopher Meyer, Laima Gerlitz

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European Ports are about to take an important step towards their future economic development. Existing legislatives such as the European Green Deal are changing the perspective on ports as individual logistic institutions and demand a more holistic view on ports in their characteristic as ecosystem involving several different actors in an interdisciplinary and multilevel approach. A special role is taken by small and medium-sized ports facing the same political restriction and future goals - such as reducing environmental impacts with 2030 and 2050 as targets - while suffering from low financing capacity, outdated infrastructure, low innovation measures and missing political support. In contrast, they are playing a key role in regional economic development and cross-border logistics as well as facilitator for the regional hinterland. Also, in comparison to their big counterparts, small and medium-sized ports are often located within or close to city areas. This does not only bear more challenges especially when it comes to the environmental performance, but can also carry out growth potentials by putting the city as a key actor into the port ecosystem. For city development, the Smart City concept is one of the key strategies currently applied mostly on demonstration level in selected cities. Hence, the basic idea behind is par to the Smart Port concept. Thus, this paper is analysing potential synergetic effects resulting from the application of Smart City and Smart Port concepts for small and medium-sized ports' ecosystems closely located to cities with focus on innovation application, greening measurements and economic performances as well as strategic positioning of the ports in Smart City initiatives.

Keywords: port-city ecosystems, regional development, sustainability transition, innovation policy

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Authors: Muhammad Ali

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Cyber-attacks and anomaly detection on the Internet of Things (IoT) infrastructure is emerging concern in the domain of data-driven intrusion. Rapidly increasing IoT risk is now making headlines around the world. denial of service, malicious control, data type probing, malicious operation, DDos, scan, spying, and wrong setup are attacks and anomalies that can affect an IoT system failure. Everyone talks about cyber security, connectivity, smart devices, and real-time data extraction. IoT devices expose a wide variety of new cyber security attack vectors in network traffic. For further than IoT development, and mainly for smart and IoT applications, there is a necessity for intelligent processing and analysis of data. So, our approach is too secure. We train several machine learning models that have been compared to accurately predicting attacks and anomalies on IoT systems, considering IoT applications, with ANOVA-based feature selection with fewer prediction models to evaluate network traffic to help prevent IoT devices. The machine learning (ML) algorithms that have been used here are KNN, SVM, NB, D.T., and R.F., with the most satisfactory test accuracy with fast detection. The evaluation of ML metrics includes precision, recall, F1 score, FPR, NPV, G.M., MCC, and AUC & ROC. The Random Forest algorithm achieved the best results with less prediction time, with an accuracy of 99.98%.

Keywords: machine learning, analysis of variance, Internet of Thing, network security, intrusion detection

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Authors: Sima Aznavi, Poria Fajri, Hanif Livani

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Smart homes are small energy systems which may be equipped with renewable energy sources, storage devices, and loads. Energy management strategy plays a main role in the efficient operation of smart homes. Effective energy scheduling of the renewable energy sources and storage devices guarantees efficient energy management in households while reducing the energy imports from the grid. Nevertheless, despite such strategies, independently day ahead energy schedules for multiple households can cause undesired effects such as high power exchange with the grid at certain times of the day. Therefore, the interactions between multiple smart home day ahead energy projections is a challenging issue in a smart grid system and if not managed appropriately, the imported energy from the power network can impose additional burden on the distribution grid. In this paper, a central energy management strategy for a network consisting of multiple households each equipped with renewable energy sources, storage devices, and Plug-in Electric Vehicles (PEV) is proposed. The decision-making strategy alongside the smart home energy management system, minimizes the energy purchase cost of the end users, while at the same time reducing the stress on the utility grid. In this approach, the smart home energy management system determines different operating scenarios based on the forecasted household daily load and the components connected to the household with the objective of minimizing the end user overall cost. Then, selected projections for each household that are within the same cost range are sent to the central decision-making system. The central controller then organizes the schedules to reduce the overall peak to average ratio of the total imported energy from the grid. To validate this approach simulations are carried out for a network of five smart homes with different load requirements and the results confirm that by applying the proposed central energy management strategy, the overall power demand from the grid can be significantly flattened. This is an effective approach to alleviate the stress on the network by distributing its energy to a network of multiple households over a 24- hour period.

Keywords: energy management, renewable energy sources, smart grid, smart home

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Authors: Sayor Ajfar Aaron, Sajjat Hossain Abir, Ashif Newaz, Mushfiqur Rahman

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Investigating the convergence of blockchain technology and artificial intelligence, this paper examines their synergistic effects on data integrity and decision-making within smart contracts. By implementing AI-driven analytics on blockchain-based platforms, the research identifies improvements in automated contract enforcement and decision accuracy. The paper presents a framework that leverages AI to enhance transparency and trust while blockchain ensures immutable record-keeping, culminating in significantly optimized operational efficiencies in various industries.

Keywords: artificial intelligence, blockchain, data integrity, smart contracts

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Authors: Mahdi Daghmhehci Firoozjaei, Minchang Kim, Dima Alhadidi

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In this paper, we present a power profiling model for smart grid consumers based on real time load data acquired smart meters. It profiles consumers’ power consumption behaviour using the dynamic time warping (DTW) clustering algorithm. Due to the invariability of signal warping of this algorithm, time-disordered load data can be profiled and consumption features be extracted. Two load types are defined and the related load patterns are extracted for classifying consumption behaviour by DTW. The classification methodology is discussed in detail. To evaluate the performance of the method, we analyze the time-series load data measured by a smart meter in a real case. The results verify the effectiveness of the proposed profiling method with 90.91% true positive rate for load type clustering in the best case.

Keywords: power profiling, user privacy, dynamic time warping, smart grid

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Authors: Rhaed Khiati, Muhammad Hanif

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In the past decade, smart healthcare systems have been on an ascendant drift, especially with the evolution of hospitals and their increasing reliance on bioinformatics and software specializing in healthcare. Doctors have become reliant on technology more than ever, something that in the past would have been looked down upon, as technology has become imperative in reducing overall costs and improving the quality of patient care. With patient-doctor interactions becoming more necessary and more complicated than ever, systems must be developed while taking into account costs, patient comfort, and patient data, among other things. In this work, we proposed a smart hospital bed, which mixes the complexity and big data usage of traditional healthcare systems with the comfort found in soft beds while taking certain concerns like data confidentiality, security, and maintaining SLA agreements, etc. into account. This research work potentially provides users, namely patients and doctors, with a seamless interaction with to their respective nurses, as well as faster access to up-to-date personal data, including prescriptions and severity of the condition in contrast to the previous research in the area where there is lack of consideration of such provisions.

Keywords: big data, smart healthcare, distributed systems, bioinformatics

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Authors: Joo Min Kim, Dongyoun Shin

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The project Future Station (FS) seek for a deeper understanding of metro station. The main idea of the project is enhancing the underground environment by combining new architectural design with IoT technology. This research shows the understanding of the metro environment giving references regarding traditional design approaches and IoT combined space design. Based on the analysis, this research presents design alternatives in two metro stations those are chosen for a testbed. It also presents how the FS platform giving a response to travelers and deliver the benefit to metro operators. In conclusion, the project describes methods to build future metro service and platform that understand traveler’s intentions and giving appropriate services back for enhancing travel experience. It basically used contemporary technology such as smart sensing grid, big data analysis, smart building, and machine learning technology.

Keywords: future station, digital lifestyle experience, sustainable metro, smart metro, smart city

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Authors: M. Caramihai, Irina Severin

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This paper deals with the design of an intelligent control structure for a bioprocess of Hansenula polymorpha yeast cultivation. The objective of the process control is to produce biomass in a desired physiological state. The work demonstrates that the designed Hybrid Control Techniques (HCT) are able to recognize specific evolution bioprocess trajectories using neural networks trained specifically for this purpose, in order to estimate the model parameters and to adjust the overall bioprocess evolution through an expert system and a fuzzy structure. The design of the control algorithm as well as its tuning through realistic simulations is presented. Taking into consideration the synergism of different paradigms like fuzzy logic, neural network, and symbolic artificial intelligence (AI), in this paper we present a real and fulfilled intelligent control architecture with application in bioprocess control.

Keywords: bioprocess, intelligent control, neural nets, fuzzy structure, hybrid techniques

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Authors: S. M. Ali, A. Salam Khan, A. U. Khan, M. Tariq, M. S. Hussain, B. A. Abbasi, I. Hussain, U. Farid

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Environment and surrounding plays a pivotal rule in structuring life-style of the consumers. Living standards intern effect the energy consumption of the consumers. In smart grid paradigm, climate drifts, weather parameter and green environmental directly relates to the energy profiles of the various consumers, such as residential, commercial and industrial. Considering above factors helps policy in shaping utility load curves and optimal management of demand and supply. Thus, there is a pressing need to develop correlation models of load and weather parameters and critical analysis of the factors effecting energy profiles of smart grid consumers. In this paper, we elaborated various environment and weather parameter factors effecting demand of consumers. Moreover, we developed correlation models, such as Pearson, Spearman, and Kendall, an inter-relation between dependent (load) parameter and independent (weather) parameters. Furthermore, we validated our discussion with real-time data of Texas State. The numerical simulations proved the effective relation of climatic drifts with energy consumption of smart grid consumers.

Keywords: climatic drifts, correlation analysis, energy consumption, smart grid, weather parameter

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Authors: Hamed Hossein Afshari, Shahrzad Jalali, Amir Hossein Ghods, Bijan Raahemi

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This paper introduces an automated clustering solution that applies to WiFi/Bluetooth sensing data and is later used for traffic management applications. The paper initially summarizes a number of clustering approaches and thereafter shows their performance for noise removal. In this context, clustering is used to recognize WiFi and Bluetooth MAC addresses that belong to passengers traveling by a public urban transit bus. The main objective is to build an intelligent system that automatically filters out MAC addresses that belong to persons located outside the bus for different routes in the city of Ottawa. The proposed intelligent system alleviates the need for defining restrictive thresholds that however reduces the accuracy as well as the range of applicability of the solution for different routes. This paper moreover discusses the performance benefits of the presented clustering approaches in terms of the accuracy, time and space complexity, and the ease of use. Note that results of clustering can further be used for the purpose of the origin-destination estimation of individual passengers, predicting the traffic load, and intelligent management of urban bus schedules.

Keywords: WiFi-Bluetooth sensing, cluster analysis, artificial intelligence, traffic management

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Authors: W. A. D. P. Wanigasundera, P. C. B. Alahakoon

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Kandy district in Sri Lanka has small scale and rain-fed paddy farming, and highly vulnerable to climate change. In this study, the status of climate change was assessed using meteorological data and compared with the perceptions of paddy farming community. Factors affecting the adaptation to the climate smart farming were also assessed. Meteorological data for 33 years were collected and the changes over time compared with the perceptions of farmers. The temperature, rainfall and number of rainy days have increased in both locations. The onset of rains also has shifted. The perceptions of the majority of the farmers were in line with the actual changes. The knowledge and attitudes about the causes of climate change and adaptation were medium and related to level of adoption. Formulating effective communication strategies, and a collaborative approach involving state, private sector, civil society to make Sri Lankan agriculture ‘climate-smart’ is urgently needed.

Keywords: adaptation of climate-smart technology, climate change, perception, rain-fed paddy

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Authors: Abdulkader Helwan

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Rheumatoid joint inflammation is characterized as a perpetual incendiary issue which influences the joints by hurting body tissues Therefore, there is an urgent need for an effective intelligent identification system of knee Rheumatoid arthritis especially in its early stages. This paper is to develop a new intelligent system for the identification of Rheumatoid arthritis of the knee utilizing image processing techniques and neural classifier. The system involves two principle stages. The first one is the image processing stage in which the images are processed using some techniques such as RGB to gryascale conversion, rescaling, median filtering, background extracting, images subtracting, segmentation using canny edge detection, and features extraction using pattern averaging. The extracted features are used then as inputs for the neural network which classifies the X-ray knee images as normal or abnormal (arthritic) based on a backpropagation learning algorithm which involves training of the network on 400 X-ray normal and abnormal knee images. The system was tested on 400 x-ray images and the network shows good performance during that phase, resulting in a good identification rate 97%.

Keywords: rheumatoid arthritis, intelligent identification, neural classifier, segmentation, backpropoagation

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Authors: Taha Benarbia

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The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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Authors: Saeid Asghari

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The growing interest in sustainability and healthy lifestyles has stimulated the development of solutions that promote mindful consumption and healthier choices. One such solution is the use of transparent graded lanes in product packaging, which enables consumers to visually track their product consumption and encourages portion control. However, the extent to which this packaging affects consumer behavior, trust, and loyalty towards a product or brand, as well as the effectiveness of messaging on the graded lanes, remains unclear. The research aims to examine the impact of transparent graded lanes on consumer behavior, trust, and loyalty towards products or brands in the context of the Janbo chain supermarket in Tehran, Iran, focusing on Ketchup and edible oils containers. A representative sample of 720 respondents is selected using quota sampling based on sex, age, and financial status. The study assesses the effect of messaging on the graded lanes in enhancing consumer recall and recognition of the product at the time of purchase, increasing repeat purchases, and fostering long-term relationships with customers. Furthermore, the potential outcomes of using transparent graded lanes, including the promotion of healthy consumption habits and the reduction of food waste, are also considered. The findings and results can inform the development of effective messaging strategies for graded lanes and suggest ways to enhance consumer engagement with product packaging. Moreover, the study's outcomes can contribute to the broader discourse on sustainable consumption and healthy lifestyles, highlighting the potential role of packaging innovations in promoting these values. We used four theories (social cognitive theory, self-perception theory, nudge theory, and marketing and consumer behavior) to examine the effect of these transparent graded lanes on consumer behavior. The conceptual model integrates the use of transparent graded lanes, consumer behavior, trust and loyalty, messaging, and promotion of healthy consumption habits. The study aims to provide insights into how transparent graded lanes can promote mindful consumption, increase consumer recognition and recall of the product, and foster long-term relationships with customers. Findings suggest that the use of transparent graded lanes on Ketchup and edible oils containers can have a positive impact on consumer behavior, trust, and loyalty towards a product or brand, as well as promote mindful consumption and healthier choices. The messaging on the graded lanes is also found to be effective in promoting recall and recognition of the product at the time of purchase and encouraging repeat purchases. However, the impact of transparent graded lanes may be limited by factors such as cultural norms, personal values, and financial status. Broadly speaking, the investigation provides valuable insights into the potential benefits and challenges of using transparent graded lanes in product packaging, as well as effective strategies for promoting healthy consumption habits and building long-term relationships with customers.

Keywords: packaging customer behavior, purchase, brand loyalty, healthy consumption

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Authors: Sami M. Alshareef

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The rapid growth of smart grid technology has brought significant advancements to the power industry. However, with the increasing interconnectivity and reliance on information and communication technologies, smart grids have become vulnerable to cyber-attacks, posing significant threats to the reliable operation of power systems. Among the critical components of smart grids, the Automatic Generation Control (AGC) system plays a vital role in maintaining the balance between generation and load demand. Therefore, protecting the AGC system from cyber threats is of paramount importance to maintain grid stability and prevent disruptions. Traditional security measures often fall short in addressing sophisticated and evolving cyber threats, necessitating the exploration of innovative approaches. Machine learning, with its ability to analyze vast amounts of data and learn patterns, has emerged as a promising solution to enhance AGC system security. Therefore, this research proposal aims to address the challenges associated with detecting and mitigating cyber-attacks on AGC in smart grids by leveraging machine learning techniques on automatic generation control of two-area power systems. By utilizing historical data, the proposed system will learn the normal behavior patterns of AGC and identify deviations caused by cyber-attacks. Once an attack is detected, appropriate mitigation strategies will be employed to safeguard the AGC system. The outcomes of this research will provide power system operators and administrators with valuable insights into the vulnerabilities of AGC systems in smart grids and offer practical solutions to enhance their cyber resilience.

Keywords: machine learning, cyber-attacks, automatic generation control, smart grid

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Authors: Vahid Bayrami Rad

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Ever since humans developed a collective way of life to the development of urbanization, the concern of security has always been considered one of the most important challenges of life. To protect property, locks have always been a practical tool. With the advancement of technology, the form of locks has changed from mechanical to electric. One of the most widely used fields of using artificial intelligence is its application in the technology of surveillance security systems. Currently, the technologies used in smart anti-theft door handles are one of the most potential fields for using artificial intelligence. Artificial intelligence has the possibility to learn, calculate, interpret and process by analyzing data with the help of algorithms and mathematical models and make smart decisions. We will use Arduino board to process data.

Keywords: arduino board, artificial intelligence, image processing, solenoid lock

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Authors: Tamara Trček Pečak, Andrej Mohar, Denis Trček

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This article investigates the latest technological means, which deploy smart structures that are based on (advanced) wireless sensors technologies and ubiquitous computing in general in order to support the above mentioned decision making. Based on two years of in-field research experiences it gives their analysis for these kinds of purposes and provides appropriate architectures and architectural solutions. Moreover, the directions for future research are stated, because these technologies are currently the most promising ones to enable cost-effective preservation of cultural heritage not only in uncontrolled places, but also in general.

Keywords: smart structures, wireless sensors, sensors networks, green computing, cultural heritage preservation, monitoring, cost effectiveness

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Authors: N. Szczepanska, B. Kudlak, G. Yotova, S. Tsakovski, J. Namiesnik

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In the scientific literature related to the widely understood issue of packaging materials designed to have contact with food (food contact materials), there is much information on raw materials used for their production, as well as their physiochemical properties, types, and parameters. However, not much attention is given to the issues concerning migration of toxic substances from packaging and its actual influence on the health of the final consumer, even though health protection and food safety are the priority tasks. The goal of this study was to estimate the impact of particular foodstuff packaging type, food production, and storage conditions on the degree of leaching of potentially toxic compounds and endocrine disruptors to foodstuffs using the acute toxicity test Microtox and XenoScreen YES YAS assay. The selected foodstuff packaging materials were metal cans used for fish storage and tetrapak. Five stimulants respectful to specific kinds of food were chosen in order to assess global migration: distilled water for aqueous foods with a pH above 4.5; acetic acid at 3% in distilled water for acidic aqueous food with pH below 4.5; ethanol at 5% for any food that may contain alcohol; dimethyl sulfoxide (DMSO) and artificial saliva were used in regard to the possibility of using it as an simulation medium. For each packaging three independent variables (temperature and contact time) factorial design simulant was performed. Xenobiotics migration from epoxy resins was studied at three different temperatures (25°C, 65°C, and 121°C) and extraction time of 12h, 48h and 2 weeks. Such experimental design leads to 9 experiments for each food simulant as conditions for each experiment are obtained by combination of temperature and contact time levels. Each experiment was run in triplicate for acute toxicity and in duplicate for estrogen disruption potential determination. Multi-factor analysis of variation (MANOVA) was used to evaluate the effects of the three main factors solvent, temperature (temperature regime for cup), contact time and their interactions on the respected dependent variable (acute toxicity or estrogen disruption potential). From all stimulants studied the most toxic were can and tetrapak lining acetic acid extracts that are indication for significant migration of toxic compounds. This migration increased with increase of contact time and temperature and justified the hypothesis that food products with low pH values cause significant damage internal resin filling. Can lining extracts of all simulation medias excluding distilled water and artificial saliva proved to contain androgen agonists even at 25°C and extraction time of 12h. For tetrapak extracts significant endocrine potential for acetic acid, DMSO and saliva were detected.

Keywords: food packaging, extraction, migration, toxicity, biotest

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Authors: Aline Alves Bandeira, Luís Pedro Lima, Maria Cecília de Paula Silva, Paulo Henrique de Viveiros Tavares

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Nowadays, the study of public policies regarding management efficiency is essential. Public policies are about what governments do or do not do, being an area that has grown worldwide, contributing through the knowledge of technologies and methodologies that monitor and evaluate the performance of public administrators. The information published on official government websites needs to provide for transparency and responsiveness of managers. Thus, transparency is a primordial factor for the execution of Accountability, providing, in this way, services to the citizen with the expansion of transparent, efficient, democratic information and that value administrative eco-efficiency. The ecologically balanced management of a Smart City must optimize environmental education, building a fairer society, which brings about equality in the use of quality environmental resources. Smart Cities add value in the construction of public management, enabling interaction between people, enhancing environmental education and the practical applicability of administrative eco-efficiency, fostering economic development and improving the quality of life.

Keywords: accountability, environmental education, new public administration, smart cities

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Authors: Chukwu J. C., Elujoba E. T., AjaniI A. A., Aiyegbayo O. O.

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Handcrafts form an integral part of the tourist experience, they represent local traditions and indigenous populations and also as valuable souvenir. The local craft sector is performing at a level far below its potential as a tourism product, hence, this paper seek to examine the challenges facing local handcraft development and suggest ways to promote and package them as souvenirs in tourist destinations in Osun state. One hundred and sixty (160) questionnaires were administered to the staffers and tourists in Osun Osogbo grove and Erin Ijesa waterfall, both in Osun state and 120 questionnaires were properly filled and returned, which gives 75% return rate. Cronbach’s Alpha was used to test the reliability of the research instrument. The findings of the study revealed that ( F_((1,118))= 2.070, r = .151, Sig.< 0.05) there exist a weak and positive relationship between local craft development and the overall development of tourist destinations in Osun state, Nigeria. Therefore, it was concluded, among others, that a lot needs to be done on packaging and promotion of the local handcraft since it was found to have a significant impact on the development of tourist destinations. This, in return, will increase the popularity and acceptability of handcraft both at home and abroad. The study recommends, among others, that government should establish a tourism entrepreneurial development centre charged with the responsibilities of creating and identifying tourism business opportunities and act as ‘one stop shop’ to purchase a local souvenir and disseminate information to potential tourist cum entrepreneurs in the tourism industry.

Keywords: packaging, promotion, handcraft, tourism, development

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Authors: Matar Celine, Gaucel Sebastien, Gontard Nathalie, Guilbert Stephane, Guillard Valerie

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To increase the very short shelf life of fresh fruits and vegetable, Modified Atmosphere Packaging (MAP) allows an optimal atmosphere composition to be maintained around the product and thus prevent its decay. This technology relies on the modification of internal packaging atmosphere due to equilibrium between production/consumption of gases by the respiring product and gas permeation through the packaging material. While, to the best of our knowledge, benefit of MAP for fresh fruits and vegetable has been widely demonstrated in the literature, its effect on shelf life increase has never been quantified and formalized in a clear and simple manner leading difficult to anticipate its economic and environmental benefit, notably through the decrease of food losses. Mathematical modelling of mass transfers in the food/packaging system is the basis for a better design and dimensioning of the food packaging system. But up to now, existing models did not permit to estimate food quality nor shelf life gain reached by using MAP. However, shelf life prediction is an indispensable prerequisite for quantifying the effect of MAP on food losses reduction. The objective of this work is to propose an innovative approach to predict shelf life of MAP food product and then to link it to a reduction of food losses and wastes. In this purpose, a ‘Virtual MAP modeling tool’ was developed by coupling a new predictive deterioration model (based on visual surface prediction of deterioration encompassing colour, texture and spoilage development) with models of the literature for respiration and permeation. A major input of this modelling tool is the maximal percentage of deterioration (MAD) which was assessed from dedicated consumers’ studies. Strawberries of the variety Charlotte were selected as the model food for its high perishability, high respiration rate; 50-100 ml CO₂/h/kg produced at 20°C, allowing it to be a good representative of challenging post-harvest storage. A value of 13% was determined as a limit of acceptability for the consumers, permitting to define products’ shelf life. The ‘Virtual MAP modeling tool’ was validated in isothermal conditions (5, 10 and 20°C) and in dynamic temperature conditions mimicking commercial post-harvest storage of strawberries. RMSE values were systematically lower than 3% for respectively, O₂, CO₂ and deterioration profiles as a function of time confirming the goodness of model fitting. For the investigated temperature profile, a shelf life gain of 0.33 days was obtained in MAP compared to the conventional storage situation (no MAP condition). Shelf life gain of more than 1 day could be obtained for optimized post-harvest conditions as numerically investigated. Such shelf life gain permitted to anticipate a significant reduction of food losses at the distribution and consumer steps. This food losses' reduction as a function of shelf life gain has been quantified using a dedicated mathematical equation that has been developed for this purpose.

Keywords: food losses and wastes, modified atmosphere packaging, mathematical modeling, shelf life prediction

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Authors: Ahmad Ghanem, Mohamad Yasin, Mona Abdel Rehim, Fabrice Gouanve, Eliane Espuche

Abstract:

Biodegradable polymers are of great interest, especially for biomedical and packaging applications. Current research efforts are focused on the development of biopolymers with the purpose of reducing the plastic pollution induced by the widely used in biodegradable polyolefins. The main challenge is focused on the elaboration of biopolymers having properties competitive to those of polyolefins. On the other hand, graphene oxide (GO), a graphene derivative, is characterized by the presence of several functional groups on the surface such as carboxylic, hydroxyl and epoxide. This feature enables modification of GO surface with different modifiers to obtain versatile surface properties and overcome the problem of graphene sheets aggregations during inclusion in a polymer matrix. In this context, poly (butylene succinate) (PBS) as promising biopolyester is modified through blending with different ratios of functionalized (GO) to improve its barrier properties. Modification of GO has been carried out using different hyperbranched polymeric structures in order to increase miscibility of the nanosheets in the hosting polymeric matrix. Films have been prepared from the modified PBS and their mechanical, thermal and gas barrier properties were investigated. The results reveal enhancement in the thermal and mechanical properties beside observed improvement of the barrier properties for the films prepared from the modified PBS. This improvement is related to the strong dependence on tortuosity effects of dispersion, exfoliation levels of fillers into the polymer matrix and interactions between the fillers and the polymer matrix.

Keywords: gas barrier properties, graphene oxide, food packaging, transport properties

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Authors: Suneet Jagdev, Siddharth Singhal, Dhrubajyoti Bordoloi, Peesari Vamshidhar Reddy

Abstract:

There is no universally accepted definition of what constitutes a Smart City. It means different things to different people. The definition varies from place to place depending on the level of development and the willingness of people to change and reform. It tries to improve the quality of resource management and service provisions for the people living in the cities. Smart city is an urban development vision to integrate multiple information and communication technology (ICT) solutions in a secure fashion to manage the assets of a city. But most of these projects are misinterpreted as being technology projects only. Due to urbanization, a lot of informal as well government funded settlements have come up during the last few decades, thus increasing the consumption of the limited resources available. The people of each city have their own definition of Smart City. In the imagination of any city dweller in India is the picture of a Smart City which contains a wish list of infrastructure and services that describe his or her level of aspiration. The research involved a comparative study of the Smart City models in India and in China. Behavioral changes experienced by the people living in the pilot/first ever smart cities have been identified and compared. This paper discussed what is the target of the quality of life for the people in India and in China and how well could that be realized with the facilities being included in these Smart City projects. Logical and comparative analyses of important data have been done, collected from government sources, government papers and research papers by various experts on the topic. Existing cities with historically grown infrastructure and administration systems will require a more moderate step-by-step approach to modernization. The models were compared using many different motivators and the data is collected from past journals, interacting with the people involved, videos and past submissions. In conclusion, we have identified how these projects could be combined with the ongoing small scale initiatives by the local people/ small group of individuals and what might be the outcome if these existing practices were implemented on a bigger scale.

Keywords: behavior change, mission monitoring, pilot smart cities, social capital

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Authors: Menonjyoti Kalita, Pradip Baishya

Abstract:

In recent times, the world has been facing serious environmental concerns and issues, such as sustainability and cost, due to the overproduction of synthetic materials and their participation in degrading the environment by means of industrial waste and non-biodegradable characteristics. As such, biocomposites come in handy to ease such troubles. Bio-based composites are promising materials for future applications for substituting synthetic packaging materials. The challenge of making packaging materials lighter, safer and cheaper leads to investigating advanced materials with desired properties. Also, awareness of environmental issues forces researchers and manufacturers to spend effort on composite and bio-composite materials fields. This paper explores and tests some nature-friendly materials has been done which can replace low-density plastics. The materials selected included sugarcane bagasse, areca palm, and bamboo leaves. Sugarcane bagasse bamboo leaves and areca palm sheath are the primary material or natural fibre for testing. These products were processed, and the tensile strength of the processed parts was tested in Micro UTM; it was found that areca palm can be used as a good building material in replacement to polypropylene and even could be used in the production of furniture with the help of epoxy resin. And for bamboo leaves, it was found that bamboo and cotton, when blended in a 50:50 ratio, it has great tensile strength. For areca, it was found that areca fibres can be a good substitute for polypropylene, which can be used in building construction as binding material and also other products.

Keywords: biodegradable characteristics, bio-composites, areca palm sheath, polypropylene, micro UTM

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Authors: Lu Zhao, Yanrong Kang, Lili Guo, Yuan Long, Guidong Xing

Abstract:

Smart watches, as a handy device with rich functionality, has become one of the most popular wearable devices all over the world. Among the various function, the most basic is health monitoring. The monitoring data can be provided as an effective evidence or a clue for the detection of crime cases. For instance, the step counting data can help to determine whether the watch wearer was quiet or moving during the given time period. There is, however, still quite few research on the analysis of human character based on these data. The purpose of this research is to analyze the health monitoring data to distinguish the drinking state from normal state. The analysis result may play a role in cases involving drinking, such as drunk driving. The experiment mainly focused on finding the figures of smart watch health monitoring data that change with drinking and figuring up the change scope. The chosen subjects are mostly in their 20s, each of whom had been wearing the same smart watch for a week. Each subject drank for several times during the week, and noted down the begin and end time point of the drinking. The researcher, then, extracted and analyzed the health monitoring data from the watch. According to the descriptive statistics analysis, it can be found that the heart rate change when drinking. The average heart rate is about 10% higher than normal, the coefficient of variation is less than about 30% of the normal state. Though more research is needed to be carried out, this experiment and analysis provide a thought of the application of the data from smart watches.

Keywords: character analysis, descriptive statistics analysis, drink state, heart rate, smart watch

Procedia PDF Downloads 149