Processing Options Research Articles

О ПРИМЕНЕНИИ СПЕКТРОЗОНАЛЬНОЙ ВИЗУАЛИЗАЦИИ В ДИСТАНЦИОННОМ ЗОНДИРОВАНИИ ЗЕМЛИ

The issues of using multispectral imaging in remote sensing of the Earth, both using satellite images and using unmanned aerial vehicles (UAVs), are discussed. The use of multispectral images for assessing reforestation, the effectiveness of herbicide use, reconstruction of archaeological sites, environmental monitoring of the surface of reservoirs by monitoring the extent of the spread of blue-green algae, and recognition of the road network in forestry is described. The feasibility of using UAVs to survey individual areas of the terrain instead of obtaining images from satellites is assessed. The results of increasing the information content of multispectral images obtained using various processing options are presented. Based on the results of the analytical review, trends in the development of methods for improving the visual quality of multispectral images obtained during monitoring of the earth's surface are formulated. The disadvantages of the considered methods for increasing the information content of multispectral images are indicated, and improvements are proposed that can improve the methods used.

Review: Inadequate Post-Harvest Processing in PNG Forest and Wood Sectors

Papua New Guinea (PNG) is blessed with a wide range of natural resources, including forestry and lumber. However, unfortunately, the nation is losing out on millions of jobs and billions of dollars in income by exporting these resources in their unprocessed form instead of taking advantage of downstream processing. PNG has the world’s third-largest rainforest, covering 33.6 million hectares and comprising 72.5% of the country’s total land area. It is imperative that the government of PNG makes the most of this valuable natural resource. The raw logging market was once profitable, but it has been in decline since China became PNG’s primary export market in 2009. To find a new source of income, the Forest Revenue Review Team (FRRT) evaluated several processing options, including the construction of large-scale plants for exporting veneer, plywood, and medium-density fiberboard (MDF), sawmills of different sizes, and a small sawmill integrated with a joinery facility. However, implementing these solutions presents various challenges, including the high-cost structure of the PNG economy and the need for national forestry legislation and policy enforcement. To ensure sustainable development and address these obstacles, it is crucial to maximize the value of PNG’s forest resources and economy by encouraging downstream processing of forestry and wood. PNG can achieve economic growth and environmental protection by promoting equitable and sustainable development, monitoring international market trends, and resolving specific issues regarding downstream processing. Despite the challenges, PNG is taking steps to advance value addition and sustainable methods in the forestry industry.

ПІДГОТОВКА МОДЕЛЮВАННЯ ФРЕЗЕРНОЇ ОБРОБКИ ДЕТАЛІ,ВСТАНОВЛЕНОЇ У ФРАКТАЛЬНИХ ЛЕЩАТАХ

The article is a publication of scientific and methodical character. The article is devoted to the preparation of a virtual experiment of milling processing of a complex profile part, which is installed in a fractal vice. It was determined that fractal vices are presented on the technological equipment market in a very limited range. At the same time, the cost of fractal vices is unreasonably high. The cost is commensurate with the cost of the milling machine itself. However, modeling the processing of a part mounted in a fractal vise is of considerable academic interest. Fractal vices use Pascal's law on the plane (with some assumptions). The mathematical model proposed earlier was further developed. The model is flat and consists of a system of three differential equations of the second order. The equations describe plane-parallel and torsional movements of the part. Selected main parameters and their recommended values for the mathematical model of the processing process. At this stage, the main goal of the virtual experiment is to compare the set and real trajectories of the milling cutter. Also, the goal is to analyze the influence of parameters of elastic-damping elements, clamping force, etc. on the result. A matrix of options for conducting a virtual experiment is proposed. The matrix provides a large number of possible movements of the cutter relative to the part (simple, complex, locked, unlocked). It was determined that the matrix of options allowsfor a large number of possible processing options. From this set, several options are selected, the most suitable for further modeling and comparison with the results of a natural experiment. It is believed that the technological system "machine –vice –tool –workpiece" is a closed dynamic system with negative feedback. However, it is necessary to investigate the behavior of the system without feed-back and compare it with the rest of the experiments

Оптимизация технологии обогащения бедной технологически упорной золото-углеродсодержащей руды

The processing of refractory gold ores is a challenging task. Refractory ores include ores that cannot be easily processed due to the fine dissemination of gold in sulphide minerals and the presence of preg-robbing carbonaceous matter. Two processes have been studied: flotation of low-grade double refractory gold ore ­using new carbon depression reagents; gravity – cleaner flotation of rougher flotation concentrate followed by pressure oxidation and the CIL treatment of POX cakes. The study is aimed to optimize the processing of low-grade (Au 0.6 g/t) refractory gold ore and achieve high process parameters. The study included the following steps: the reduction of organic carbon mass fraction (< 0.6 %) in concentrates reporting to hydrometallurgical treatment; experiments on the hydrometallurgical treatment of flotation concentrates using two process options: pressure oxidation (POX) of the initial flotation concentrate followed by the CIL treatment of POX cakes and preliminary gravity – cleaner flotation of the initial flotation followed by pressure oxidation and the CIL treatment of POX cakes. The research methodology is based on studying the influence of carbon depressant reagents on the flotation properties of organic carbon during the flotation process. When carrying out flotation experiments, the equipment of JSC Irgiredmet was used, installed at the semi-industrial testing site (laboratory mills, mechanical flotation machines and auxiliary equipment). The study is carried out in accordance with generally accepted methods of ore preparation and flotation concentration. The mass fraction of organic carbon in the flotation concentrate decreased from 2.0 to 0.5 %. It has been achieved by the use of new reagents for carbon depression (carbon depression reagents). The products of refractory gold ore flotation using new reagents for carbon depression were flotation concentrates suitable for further hydrometallurgical treatment. According to the experiments on rougher flotation concentrate pressure oxidation and subsequent POX cake cyanide leaching, the recovery of gold on the carbon adsorbent was 83.5 %. Preliminary gra­vity – cleaner flotation of the concentrate before pressure oxidation improved the loading of gold on the carbon adsorbent to 96.6 %.

Processing of Electronic Scrap with Ausmelt TSL Technology

Continued decreasing of the world’s average copper ore grades, coupled with a meteoric rise in the generation of consumer waste streams, has led to the processing of electronic scrap (e-scrap) and other secondaries assuming increasing importance within the global copper industry. Treatment of these secondary feeds has traditionally been carried out in the Blast furnace, Peirce-Smith converter and/or anode furnace. More recently however, bath smelting processes such as the Ausmelt TSL and Outotec Kaldo technologies have emerged as the preferred option for processing these materials due to their superior environmental performance and flexibility to operate under a wide range of conditions. Furthermore, the ability of these processes to handle a wide range of feed inputs make them ideally placed for the processing of not only e-scrap but also other waste streams from the clean energy transition such as end of life e-mobility batteries and photovoltaic systems. This paper focuses on the processing of electronic scrap and other copper secondaries with Ausmelt TSL technology and discusses specific issues facing secondary copper smelters in relation to impurity management and process offgas handling/cleaning.

Acid and ammonia leaching of secondary copper sulfides

The study focuses on understanding the efficiency and kinetics of copper recovery from secondary sulphide ores, which are increasingly becoming a significant source of copper. An experimental investigation was undertaken to assess the leaching behaviour of secondary copper sulphides in acid and ammonia media. The test work consisted of ore sample characterisation, including physico-mechanical properties determination, chemical assay, whole rock analysis, mineralogy, and copper distributions, followed by acid consumption tests, agglomeration, and agitation leach tests. Leaching tests were conducted in a lab-scale agitated reactor using 100 g of the ore sample, 0.3 l of leach solution, а stirring rate of 420 rpm and a leach time of up to 200 hours. The effect of the reaction time and oxidant (Fe3+, NO+) concentration on the copper recovery was evaluated. The maximum copper extraction was obtained in the test performed using acid media with the addition of NO+ as an oxidant. Further, a potential hydrometallurgical process option for recovering copper from secondary sulphide sources is proposed.

Agriculture Data Platform – Institutional Data Repository – Selected Aspects

This paper presents selected aspects of a data platform to store agricultural data. It analyses the key user and system requirements for the data platform. The presented aspects were identified through a literature review, interviews and discussions with selected data experts and researchers and future users of the platform. The following issues of the data platform are discussed in the paper: architecture, data types, data source types, metadata, disciplinary interfaces, data sharing, data reusability, Open Science, FAIR data principles, and further data processing options. Part of the knowledge from this article was used in the design and implementation of the Institutional Data Repository called Data Management Platform (DaMP.) CZU (Czech University of Life Sciences Prague) (OPENAI, 2023).

Solvent-assisted recrystallisation for the recovery of cannabinoids from Cannabis extraction by-products

A wax by-product removed from the initial stages of commercial Cannabis processing, which contains significant amounts (39–51% (w/w)) of cannabinoids, is currently underutilised due to a lack of information on wax composition and further processing options. Significant value might be generated from further recovery of the cannabinoids entrapped within the wax fraction, and from further processing of the wax into useable products. This study aimed to develop a method to recover the cannabinoids contained in the wax and to prepare the wax for further refinement into a valuable product. A method where the wax by-product was dissolved in ethyl acetate and then recrystalized was developed, which consisted of a heating and mixing stage followed by filtering and washing with additional solvent. The main variables for the experiments were the ratio of solvent to wax for dilution, and the ratio of solvent to wax for post-crystallisation washing. The recrystallisation method was successful in recovering the cannabinoids from the wax and the effectiveness of the recovery was significantly impacted by the solvent addition. The method was validated on two samples of industrial by-products sourced from the cannabinoid extraction industry, and the highest recovery over two consecutive dissolution-recrystallisation cycles was 68.3% and 96.3%, for wax A and B respectively. In both cases, maximum recoveries were achieved with the experiments corresponding with the highest solvent addition. It was therefore concluded that the use of more solvent during recrystallisation, especially for the washing step during filtering, was favourable as it resulted in a higher recovery of cannabinoids from the wax by-product. Furthermore, wax carry-over to the recovered filtrate was sufficiently low (< 3% (w/w)), and was easily removed by centrifugation. The majority of the carried-over lipophilic components were fatty acids, with a maximum concentration of 17.39 mg/g in the filtrate removed after the first stage of recrystallisation with wax A. The other components (n-alkanes, fatty alcohols) were in significantly lower abundance compared to the fatty acid fraction. The recovery when the wax was filtered without undergoing recrystallisation was 33.5%, significantly less than the recovery of the recrystallisation method. This work successfully demonstrated a methodology for simple cannabinoid recovery from Cannabis processing by-products, with the potential to create significant additional value from what is currently regarded as a waste in this industry.

Value chain analysis of potato in Bajhang district, Nepal

The study was conducted in the Bajhang district from February to July 2022. Its goals were to find the key actors in the potato value chain, assess their linkage, analyse marketing margins, determine the share of value-addition among each actor, evaluate the production cost, productivity, and profitability of producers, examine the producer’s share in consumer rupees, and conduct a SWOT analysis. The data collection process involved the random purposive sampling technique to select a total of 80 potato producers, 5 aggregators, 5 wholesalers, 10 retailers, 50 consumers, and 3 extension service providers. Findings revealed that, on average, potato cultivation covered 0.215 hectares (4.23 Ropani) with a productivity of 13.46 Mt/ha, which is lower than the national average. The production cost of the producer was NRs. 301,756.60/Ha (NRs. 15,356.57/Ropani) with a benefit-cost ratio of 1.37, and the producer’s share was 51.68%. The primary value chain actors included input suppliers, producers, aggregators, wholesalers, retailers, and consumers. Marketing margins for producers, aggregators, wholesalers, and retailers were NRs. 359.25/quintal, NRs. 965/quintal, NRs. 945/quintal, and NRs. 1170/quintal, respectively. Value addition by potato producers accounted for 10.45%, while aggregators, wholesalers, and retailers contributed 28.05%, 27.48%, and 34.02%, respectively. The SWOT analysis highlighted opportunities like favourable policies, subsidies, processing options, rising potato demand, and potential production area expansion. To boost the profitability of the potato industry, it is imperative to address challenges such as poor seed quality, diseases-pests, drought, short shelf life, soil degradation, and fertilizer and pesticide availability while strengthening the linkage of value chain actors.

Modelling dense particle streams during free-fall electrostatic separation

Electrostatic particle separation is an attractive option for dry processing in the resource and recycling industries. Free-fall electrostatic separators are particularly simple and versatile member of this family of technologies. This paper presents numerical simulations of the movement of particles with different charges and masses within a stream of other particles in an electric field. The modelled system comprises much larger numbers and higher spatial densities of particles than previous models, and allows a realistic assessment of the effect of interparticle electrostatic forces and collisions. The effect of an angled feed with both co- and counter-directional fields is investigated, and the results translated to grade-recovery curves for different configurations. Among the important results were the degradation of separation performance with particle feed rate, the potential importance of Coulombic interparticle reactions in dense particle streams, and the benefits of an angled feed with a counter-directional electric field.

Анализ методов подготовки и преобразования информации, поступающей в хранилища данных для эффективного управления горнотехнической системой

The article assesses the existing methods of data collection and processing in the industry and proposes an alternative option of data processing to manage mining engineering systems at various stages of their operation. It is demonstrated that the formed volume of information that comes with different frequency rates and requires dedicated processing, structuring and analysis methods forms a system of big data and serves to enhance the efficiency of implementing geotechnical processes. A possible unified structure of data acquisition from digital sources of mining engineering system is presented. An analysis is provided of possible methods to process data for analytical purposes and for searching implicit dependencies and solving problems of predictive analytics. Tools for data collection and storage are proposed to create a unified system of big data analysis for management of mining engineering systems. It is stated that in order to create a unified analytical system for collection of digital data from a mining system, it is necessary to use standard industrial protocols for data collection and storage, for instance MQTT, used as an industry standard in the Industrial Internet of Things (IIoT) systems in accordance with requirements of ISO/ IEC 20922:2016. Storage requires the use of a conventional queue broker architecture, as well as a tool for working with the time series which is required to apply machine learning and big data methods. The approach to data classification in terms of the data acquisition speed proposed in the article makes it possible to standardize the data handling principles. Since the volume of transmitted data does not depend on the frequency of acquiring information from a digital source, it is proposed to transmit all the generated data from a digital source for subsequent search of implicit dependencies between the data. It is noted that application of specific methods and algorithms to analyze data of a mining system depends primarily on the task set which is often formed as a hypothesis to be tested by identifying implicit dependencies between different data sources. In order to improve the efficiency of managing a mining system at all the stages of field development, it is proposed to apply the ELT approach, which can be an important advantage in terms of controlling the technological processes of the mining system in the future.

Overcoming thermal instability of polymeric Core-Shell-Particles: Advanced processing options for the preparation of Stimuli-Responsive structural color materials

Core-shell particles (CSP) represent one of the most promising building blocks for the artificial production of stimuli-responsive materials with iridescent structural colors. Despite tremendous efforts in the past two decades, scalable processing options for CSP are overall rare and mostly limited to 2D structures in the form of films and foils. This work investigates why common large-scale polymer-processing techniques, such as injection molding or fused filament fabrication, are hardly applicable to state-of-the-art CSP: While rheological prerequisites are fulfilled, thermal stability is proven to be surprisingly poor. Temperature instability during processing is caused by a thermally induced cross-linking reaction of residual reactive moieties. This undesired cross-linking reaction can be efficiently suppressed via optimizations of the particle architecture, in terms of adjusting the core-to-shell ratio and number of grafting anchors. Thermal stability can be further increased upon incorporation of primary antioxidants. The theoretical framework and the feasibility of the developed solution strategies are verified by a variety of thermoanalytical methods, including differential scanning calorimetry, thermogravimetric analysis, as well as rheological and mechanical measurements. Finally, advanced CSP are developed and demonstrated to be conveniently processable at elevated temperatures of up to 250 °C. These next-generation CSP formulations are advantageous for established processing techniques and may further pave the way for the design of new large-scale methods suitable for industrial use. Potential applications are smart sensors, advanced display technologies, or anti-counterfeiting materials.

Technology Development for the Pyrolysis of Hydrocarbons in Liquid Metal

AbstractThis article describes the development of a new technology based on the application of liquid metal and aims to produce hydrogen by decarbonization (pyrolysis process) of both natural and artificially synthesized hydrocarbons. When biogas with a sufficiently high carbon dioxide content is used as a feedstock, or by the targeted addition of CO2 to methane, a mixture of hydrogen and carbon monoxide (synthesis gas) can be produced. Furthermore, the paper describes another very interesting application of the technology to create negative emissions. In this scenario, the processes direct air capture, methanation, electrolysis and methane pyrolysis are combined to synthesize solid carbon from atmospheric CO2. The broad range of process options investigated indicates that, when the technology is scaled up to industrial scale, the result will be a process that is flexible in both the use of reactants and the resulting products.

A Bayesian hierarchical model for the inference between metal grade with reduced variance: Case studies in porphyry Cu deposits

Ore sorting is a preconcentration technology and can dramatically reduce energy and water usage to improve the sustainability and profitability of a mining operation. In porphyry Cu deposits, Cu is the primary target, with ores usually containing secondary ‘pay’ metals such as Au, Mo and gangue elements such as Fe and As. Due to sensing technology limitations, secondary and deleterious materials vary in correlation type and strength with Cu but cannot be detected simultaneously via magnetic resonance (MR) ore sorting. Inferring the relationships between Cu and other elemental abundances is particularly critical for mineral processing.The variations in metal grade relationships occur due to the transition into different geological domains. This raises two questions - how to define these geological domains and how the metal grade relationship is influenced by these geological domains. In this paper, linear relationship is assumed between Cu grade and other metal grades. We applies a Bayesian hierarchical (partial-pooling) model to quantify the linear relationships between Cu, Au, and Fe grades from geochemical bore core data. The hierarchical model was compared with two other models - ‘complete-pooling’ model and ‘no-pooling’ model. Mining blocks were split based on spatial domain to construct hierarchical model. Geochemical bore core data records metal grades measured from laboratory assay with spatial coordinates of sample location. Two case studies from different porphyry Cu deposits were used to evaluate the performance of the hierarchical model. Markov chain Monte Carlo (MCMC) was used to sample the posterior parameters. Our results show that the Bayesian hierarchical model dramatically reduced the posterior predictive variance for metal grades regression compared to the no-pooling model. In addition, the posterior inference in the hierarchical model is insensitive to the choice of prior. The data is well-represented in the posterior which indicates a robust model. The results show that the spatial domain can be successfully utilised for metal grade regression. Uncertainty in estimating the relationship between pay metals and both secondary and gangue elements is quantified and shown to be reduced with partial-pooling. Thus, the proposed Bayesian hierarchical model can offer a reliable and stable way to monitor the relationship between metal grades for ore sorting and other mineral processing options.

Further Validation of a Self‐administered Smartphone‐based Verbal Learning and Memory Assessment

AbstractBackgroundThe International Shopping List test (ISLT) is a verbal word list learning test set within a realistic shopping list context, supporting ease of cultural adaptation, and addressing content validity and patient relevance. Improvements to and the wide adoption of natural language processing (NLP) software has enabled the possibility for self‐administered tests of verbal learning. LilaTM a self‐administered, smartphone‐application (app) was developed, using the virtual assistant and NLP. We have previously reported acceptability and usability data from qualitative analysis of concept elicitation interviews. We now seek to provide preliminary validation data around its use.MethodA convenience sample of healthy young adults (n = 40), M(SD)age = 35 (16), were invited to install and complete one assessment of the LilaTM app. A usability survey was also administered to explore participants’ experiences. The sample was predominantly female (70%) and of Asian ethnicity (62.5%). Data were collected in Australia, using an English word pool developed for the USA.ResultAcceptability was generally high with N = 38 completing immediate recall rounds and N = 32 completing the delayed recall round. Eight‐two percent found it extremely or somewhat easy to hear and understand what items were on the shopping list and 95% indicated that it was extremely or somewhat easy to understand what they had to do to complete the assessment. Scoring accuracy was 88% at the word item level, with reprocessing to address accent, context setting, and other NLP approaches to improve accuracy underway e.g., homophones biased to the grocery item.ConclusionWhilst acceptability was high, the importance of localization of test stimuli was confirmed as well as the need for additional data processing options to account for accent. Continued optimization of data processing to score participant responses and word item pools to reduce ambiguity is expected to further improve accuracy e.g., accounting for regional accents and consideration of homophones and compound words. However, specific characteristics of speech including in those for whom English may be a second/foreign language will be an area of focus for future development.

Further Validation of a Self‐administered Smartphone‐based Verbal Learning and Memory Assessment

AbstractBackgroundThe International Shopping List test (ISLT) is a verbal word list learning test set within a realistic shopping list context, supporting ease of cultural adaptation, and addressing content validity and patient relevance. Improvements to and the wide adoption of natural language processing (NLP) software has enabled the possibility for self‐administered tests of verbal learning. LilaTM a self‐administered, smartphone‐application (app) was developed, using the virtual assistant and NLP. We have previously reported acceptability and usability data from qualitative analysis of concept elicitation interviews. We now seek to provide preliminary validation data around its use.MethodA convenience sample of healthy young adults (n = 40), M(SD)age = 35 (16), were invited to install and complete one assessment of the LilaTM app. A usability survey was also administered to explore participants’ experiences. The sample was predominantly female (70%) and of Asian ethnicity (62.5%). Data were collected in Australia, using an English word pool developed for the USA.ResultAcceptability was generally high with N = 38 completing immediate recall rounds and N = 32 completing the delayed recall round. Eight‐two percent found it extremely or somewhat easy to hear and understand what items were on the shopping list and 95% indicated that it was extremely or somewhat easy to understand what they had to do to complete the assessment. Scoring accuracy was 88% at the word item level, with reprocessing to address accent, context setting, and other NLP approaches to improve accuracy underway e.g., homophones biased to the grocery item.ConclusionWhilst acceptability was high, the importance of localization of test stimuli was confirmed as well as the need for additional data processing options to account for accent. Continued optimization of data processing to score participant responses and word item pools to reduce ambiguity is expected to further improve accuracy e.g., accounting for regional accents and consideration of homophones and compound words. However, specific characteristics of speech including in those for whom English may be a second/foreign language will be an area of focus for future development.

OPTIMASI PROSES PENETRALAN AIR ASAM TAMBANG PADA SETTLING POND PT DARMA HENWA TBK JOBSITE PT ARUTMIN INDONESIA SITE ASAM-ASAM

One of method which ussualy used in neutralizing Acid Mine Drainage using neutralizing agents is Settling Pond. This treatment process requires adding neutralizing agents to the waters or through a mixing system and allowing deposits to form in the pond. Many factors and process mechanisms can affect the effluent quality of an Acid Mine Drainage processing system. The purpose of this study is to evaluate the effectiveness and optimize the Acid Mine Drainage neutralization process carried out in Settling Pond 19. The research method used is to make theoretical simulations both modeling using PHREEQC and calculations to simulate various neutralization process options. The results showed that the neutralization process was affected by the quality of the neutralizing agent, the number of doses, the saturation index (precipitation) limit, the dissolution process of the neutralizing agent, the duration of dosing, and the duration of neutralization. According to modeling and theoretical calculations, the technical recommendations for optimizing the Acid Mine Drainage neutralization process to produce effluent quality that meets wastewater quality standards are the duration interval to inject neutralizer from every 60 minutes to every 13.6 minutes with a continuous dosing mechanism; The use of a maximum dose of limestone of 0.22 g/L to avoid oversaturated events, and the use of a limestone dissolution mechanism before the injection process is carried out to reduce the need for retention time for 216 seconds.

Emergency Shutdown Valve damage classification by machine learning using synthetic data

Emergency Shutdown Valves (EDSVs) are used in industrial applications to interrupt internal fluid flow in pipelines during hazardous events. During their operation, these valves can suffer cumulative damage on their reinforced polytetrafluoroethylene (RPTFE) seats that can put their operation and effectiveness at risk. One of the options for detecting the occurrence of damage is to analyse data acquired from fluid pressure and torque sensors during the closing and opening cycles of the valve. The resulting operational signatures are commonly evaluated through so-called Transition Points (TPs) that are manually marked in a subjective manner by a trained operator. In addition to being slow and laborious, this approach discards most of the acquired information. Alternatives to this method would be the use of Damage Indexes (DIs) that are extracted from the signatures, or even the evaluation of the complete pressure or torque signature. These methods, when associated with machine learning (ML) algorithms, could use the acquired information more efficiently and reliably, and would have the potential to completely automate the monitoring process. In this work, these three processing options were tested and compared using real and synthetic data that were generated with the Monte Carlo (MC) method. The results indicate that the evaluation of the complete signature with a Gradient Boosting Classifier (GBC) algorithm would be the most effective strategy, which correctly detects the damage in 99% of the cases considered.

A Comprehensive Survey on Internet of Things for Smart Cities : Applications, Communication Protocols, Network Types and Requirements

Rapid population growth in recent decades has made it imperative to find innovative answers to pressing problems in areas like transportation, healthcare, energy, and public works. One of the most interesting technology enablers for meeting these difficulties is the Internet of Things (IoT), which involves the global interconnection of a vast quantity of items equipped with electronics, software, sensors, and network connections. The IoT is a cutting-edge contemporary technology that has the potential to link a wide variety of digital objects to the web, enabling a wide variety of new services within the context of a "smart city". These gadgets come equipped with a wide range of sensing, acting, and processing options. Attractive IoT technology and big data analytics are making smart city plans a reality all around the world. By improving infrastructure and transportation networks, decreasing traffic congestion, managing trash, and enhancing the quality of human life, these services are revolutionizing urban areas. When fully implemented, the IoT will allow for the seamless integration of a wide range of disparate end systems and the open sharing of data for the development of an abundance of digital services. The focus of this essay is on an urban IoT framework, a still-broad category that is yet to be characterized by its particular application domain. Actually, urban IoTs are made to support the Smart municipal concept, which seeks to apply current communication technology to supply extra services to municipal administration and people. This article, therefore, offers a comprehensive analysis of the relevant technologies, protocols, and architecture.

Spatio-temporal techno-economic assessment of the algae-based supply chain: A proof-of-concept for North-West Europe

The growing world population is in need for new sustainable resources for healthy food, animal feed and chemicals. Algae produce a variety of compounds via conversion of CO2, nutrients, and light, and offer potential as renewable feedstock. However, producing microalgae is costly. Therefore, new economically viable supply chains must be developed. A variety of techno-economic assessments (TEA) has been performed to gain insight in the economic feasibility of algae production systems and refineries. While a TEA provides insights relevant to the technical and economic feasibility of a process, geographical conditions must be considered since the regional characteristics influence process feasibility and supply chain design.This paper presents a spatio-temporal TEA by combining a dynamic TEA model and a supply chain design optimisation model, MooV. The dynamic TEA outlines the conditions of the processes to reach a techno-economic feasible case as well as mass balances and OPEX and CAPEX of the different potential processes in the chain. MooV combines these parameters with geographic specific parameters such as the locations of activities and the characteristics of the transport network to define the optimal supply chain configuration (e.g., location and process type and capacity) based on minimal cost.The approach is demonstrated by year-round cultivation of Nannochloropsis gaditana in a horizontal tubular photobioreactor in 3 regions in North-West Europe. The analysis indicates that the cost per kg DM algae output can vary considerably (±40 %) depending on the region and the set-up of the supply chain. Including geographic characteristics as well as comparing different supply chain design options are essential to come to a viable business case. The approach can also be applied to different algae strains, different regions and different process options.