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This study was conducted to supplement single and complex probiotics to investigate the effect on growing-finishing pigs and compost. In experiment 1, the 64 crossbred ([Landrace × Yorkshire] × Duroc) pigs with an initial body weight of 18.75 ± 0.33 kg and a birth of 63 days were assigned to a completely randomized four treatment groups based on the initial body weight (4 pigs in a pen with 4 replicate pens for each treatment). For 13 weeks, the dietary treatments were provided: 1) Control (CON; basal diet), 2) T1 (CON + 0.2% Bacillus subtilis), 3) T2 (CON + 0.2% Saccharomyces cerevisiae), 4) T3 (CON + 0.2% Bacillus subtilis + 0.2% Saccharomyces cerevisiae). In experiment 2, the pig manure was obtained from Chungbuk National University (Cheongju, Korea) swine farm. For 12 weeks, the supplementary treatments were provided: 1) CON, non-additive compost; 2) T1, spray Bacillus subtilis 10 g per 3.306 m2; 3) T2, spray Bacillus subtilis 40 g per 3.306 m2; 4) T3, spray Saccharomyces cerevisiae 10 g per 3.306 m2; 5) T4: spray Saccharomyces cerevisiae 40 g per 3.306 m2; 6) T5, spray Bacillus subtilis 5 g + Saccharomyces cerevisiae 5 g per 3.306 m2; 7) T6, spray Saccharomyces subtilis 20 g + S. cerevisiae 20 g per 3.306 m2 and there were 6 replicates each treatment. In experiment 1, During the overall experimental period, T3 showed significantly improved (p < 0.05) feed conversion ratio and average daily gain compared to other groups. In average maturity score, T3 showed significantly higher (p < 0.05) than other groups. Supplementing complex probiotics group improved (p < 0.05) H2S emissions and fecal microflora compared to the non-supplementing group. In experiment 2, additive probiotics groups had no effect (p > 0.05) on moisture content than the non-additive group at 9 and 12 weeks. T6 showed a significantly improved (p < 0.05) average maturity score at all periods and ammonia emissions at 1 week and 4 weeks compared to other groups. In summary, supplementation complex probiotics induced positive effects on both pigs and compost.

This experiment was conducted to investigate the effect of stimbiotic (STB) in broilers with necrotic enteritis (NE). A total of 180 one-day-old Arbor Acres (initial body weight of 34.81 ± 1.04 g) were used in this experiment for 32 days. All broilers were randomly allocated into six treatments, and each experimental group had 10 replicate cages with three broilers per cage. The experiment was conducted in a 2 × 3 factorial design consisting of two levels of challenge (challenge and non-challenge) and three levels of STB (0, 0.05, and 0.1%). The NE challenge significantly decreased (P

This study was conducted to investigate the effects of protease supplementation and different nutrient density of diets in growing-finishing pigs. A total of one hundred-eight crossbred growing pigs ([Landrace × Yorkshire] × Duroc) with an initial body weight (BW; 18.74 ± 3.46 kg) were used for 15 weeks. Pigs were randomly assigned to six dietary treatments with 6 replicates of 3 pigs per pen in a 3 × 2 factorial through the following arrangement: Three groups of protease (1, Basal diets; 2, Protease A: 125 mg/kg protease derived from Streptomyces sps; 3, Protease B: 100 mg/kg protease derived from Bacillus licheniformis) at two different nutrient density diets (1, Basal requirement; 2, 0.94%–0.98% higher than requirement in dietary protein and 50 kcal/kg in energy). High nutrient (HN) diets showed higher average daily gain (ADG) (p < 0.05) and apparent total tract digestibility (ATTD) of crude protein (CP) (p < .0001) compared to basal nutrient (BN) diets during growing periods. Supplementation of protease showed higher BW (p < 0.05) and ADG (p < 0.05) compared to non-supplementation of protease during growing periods. Also, supplementation of protease showed higher ATTD of CP (p < 0.01), ATTD of gross energy (p < 0.05) and decreased blood urea nitrogen (BUN) level (p = 0.001) compared to non-supplementation of protease during finishing periods. Pigs which fed the protease showed decreased ammonia (NH3) emissions (p < 0.05) during experiment periods and decreased hydrogen sulfide (H2S) emissions (p < 0.01) during finishing periods. Interactions between nutrient density and protease were observed, which decreased the feed conversion ratio (p < 0.05) in HN diets without protease compared to BN diets without protease during weeks 4 to 6. Also, interaction between nutrient density and protease was observed, which resulted in improved ATTD of CP (p < 0.01) in response to PTA supplementation with HN diets during the finishing period. In conclusion, supplementation of protease reduces NH3 in feces and BUN in whole blood by increasing the digestibility of CP and improves growth performance. Also, diets with high nutrient density improved growth performance and nutrient digestibility in growing periods.

Selenium (Se) is an essential trace mineral that plays an important role in physiological processes by regulating the antioxidant defense system and enhancing immunity. Chromium is an essential mineral involved in carbohydrate and lipid metabolism and also plays a role in maintaining normal insulin function. Based on these advantages, we hypothesized that the addition of selenomethionine (SeMet) and organic chromium (OC) to broiler diets would increase Se deposition, antioxidant capacity and immune response in meat. Therefore, this study analyzed the effects of OC and SeMet on growh performance, nutrients digestibility, blood profiles, intestinal morphology, meat quality characteristics, and taxonomic analysis of broilers. A total of 168 one-day-old broiler chicken (Arbor Acres) were randomly allotted to 3 groups based on the initial body weight of 37.33 ± 0.24 g with 7 replicate per 8 birds (mixed sex). The experiments period was 28 days. Dietary treatments were folloewd: Basal diets based on corn-soybean meal (CON), basal diet supplemented with 0.2 ppm OC and 0.2 ppm SeMet (CS4), and basal diet supplemented with 0.4 ppm OC and 0.4 ppm SeMet (CS8). Supplementation of OC and SeMet did not affect on growth performance, nutrient digestibility. However, CS8 supplementation increased in duodenum villus height and villus height : crypt depth, and increased in breast meat Se deposition. In addition, CS8 group showed higher uric acid and total antioxidant status than CON group. Taxonomic analysis at phylum level revealed that Proteobacteria and Firmicutes of CS4 and CS8 were lower than CON group. In genus level, the relative abundance of fecal Lactobacillus and Enterococcus of CS4 and CS8 groups were higher than CON group. In short, 0.4 ppm OC and 0.4 ppm SeMet supplementation to broiler diet supporitng positive gut microbiome change, also enhancing antioxidant capacity, and Se deposition in breast meat.

This study investigated the effect of processed forms (defatted or hydrolyzed) of black soldier fly larvae (Hermetia illucens L., BSFL) as a protein substitute on broilers. Experiment 1 was a feeding experiment, and Experiment 2 was a metabolism experiment. In Experiment 1, a total of 120 day-old Arbor Acres broilers (initial body weight 39.52 ± 0.24 g) were used for 28 days. There were 8 replicate pens, and 5 broilers were assigned to each pen. In Experiment 2, a total of 36 day-old broilers (initial body weight 39.49 ± 0.21 g) were used for the metabolism trial. There were 2 broilers in a metabolism cage and six replicate cages per treatment. The dietary treatments were as follows: a basal diet (CON), a basal diet without fishmeal and substitute with defatted BSFL (T1), a basal diet without fishmeal and a substitute with hydrolyzed BSFL (T2). In Experiment 1, during the entire experimental period, the T2 group significantly increased (p < 0.05) body weight gain and feed intake compared to the CON and T1 groups. The feed conversion ratio showed a lower tendency (p = 0.057) in the T2 group than in the CON and T1 groups. At 2 weeks, the CON and T2 groups were significantly higher (p < 0.05) crude protein (CP) digestibility than the T1 group. At 4 weeks, the total protein level significantly increased (p < 0.05) in the CON and T2 groups compared to the T1 group. In Experiment 2, the CP digestibility significantly increased (p < 0.05) in the T2 group compared to the CON and T1 group at weeks 2 and 4. At week 4 amino acid digestibility, the T2 group significantly increased (p < 0.05) lysine, methionine, tryptophan, and glycine digestibility compared to the T1 group. There was no difference in fecal microbiota among the treatment groups. In conclusion, feeding hydrolyzed BSFL as a fishmeal substitute in broiler diets improved growth performance, CP digestibility, and specific amino acid digestibility. Therefore, it is considered that hydrolyzed BSFL in broiler diets can be sufficiently used as a new protein source.

The electric vehicle (EV) industry has emerged in response to the necessity of reducing greenhouse gas emissions and combating climate change. However, as the number of EVs increases, EV charging networks are confronted with considerable obstacles pertaining to accessibility, charging time, and the equilibrium between electricity demand and supply. In this paper, we present a techno-economic analysis of EV charging stations (EVCSs) by building type. This analysis is based on public EVCS data and considers both standalone local grid operation and integrated operation of distributed energy resources (DERs) and the local grid. The analysis has significant implications for the management of the electricity grid and the utilization of sustainable energy, and can result in economic benefits for both residential, commercial, and public buildings. The analysis indicates that integrating DERs with the local grid at EV charging stations can reduce local grid usage relative to EV demand. Nevertheless, there are also complexities, such as initial investment and maintenance costs, especially the weather-dependent performance variability of solar, which require financial support mechanisms, such as subsidies or tax incentives. Future research should focus on different DER integrations, regional and seasonal variability, user behavior, installation location, policy and regulatory impacts, and detailed capital expenditure analysis. Such research will advance DER and EVCS integration and contribute to increasing the efficiency and sustainability of urban energy systems.

Animal welfare during transport became an largely issue because of increasing demand for improved animal welfare standards. Most studies on the animal welfare during transportation have concentrated on the atmosphere and the temperature of the truck compartments. Thus, the objective of study was to collect and quantify three axis acceleration and determine the effect of bedding for transporting pigs from farm to slaughterhouse. A total of 2,840 crossbred fattening pigs with a live weight of approximately 115 kg were used. They were raised in the same commercial farms and transported to the same commercial slaughterhouse. A 3×2×2 completely randomized factorial design was used to investigate effects of rubber type bedding (bedding or non-bedding) and two levels of driving style (aggressive or normal) in three different time periods with different outside temperatures. Air temperature treatments were as follow: high temperature ([HT] higher than 24°C); low temperature ([LT] lower than 10°C); normal temperature ([NT] 10°C to 24°C). In our experiment, pigs transported under aggressive driving style showed lower (p < 0.05) pH and water holding capacity (WHC) than those transported under normal driving style. Pigs transported under normal driving style showed a lower percentage of drip loss (DL) (p < 0.05) than those transported with an aggressive driving style. Also, transported with bedding showed higher (p < 0.05) lying behavior but lower (p < 0.05) sitting behavior than those transported without bedding. Pigs transported under normal driving style showed lower (p < 0.05) cortisol level than those transported under aggressive driving style. In conclusion, aggressive driving style cause acute stress in pigs, while bedding helps alleviate acute stress in pigs during transportation in LT.

Abstract Modern communication and navigation systems are increasingly relying on atomic clocks. As timing precision requirements increase, demands for lower SWaP (size, weight, and power) clocks rise. However, it has been challenging to break through the general trade-off trend between the clock stability performance and SWaP. Here we demonstrate micro mercury trapped ion clock (M2TIC) prototypes integrated with novel micro-fabricated technologies to simultaneously achieve high performance and low SWaP. The M2TIC prototypes could reach the $$10^{-14}$$ 10 - 14 -stability level in 1 day with a SWaP of 1.1 L, 1.2 kg, and under 6 W of power. This stability level is comparable to the widely used rack-mount Microchip 5071A cesium frequency standard. These standalone prototypes survived regular commercial shipping across the North American continent to a government laboratory, where their performance was independently tested. The M2TIC sets a new reference point for SWaP and performance and opens opportunities for high-performance clocks in terrestrial and space applications.

Escherichia coli (E. coli) and Salmonella enterica (SE) infections in pigs are major source associated with enteric disease such as post weaning diarrhea. The aim of this study was to investigate the effects of Pediococcus pentosaceus in weaned piglets challenged with pathogen bacteria. In Experiment.1 90 weaned piglets with initial body weights of 8.53 ± 0.34 kg were assigned to 15 treatments for 2 weeks. The experiments were conducted two trials in a 2 × 5 factorial arrangement of treatments consisting of two levels of challenge (challenge and non-challenge) with E. coli and SE, respectively and five levels of probiotics (Control, Lactobacillus plantarum [LA], Pediococcus pentosaceus SMFM2016-WK1 [38W], Pediococcus acidilactici K [PK], Lactobacillus reuteri PF30 [PF30]). In Experiment.2 a total of 30 weaned pigs (initial body weight of 9.84 ± 0.85 kg) were used in 4 weeks experiment. Pigs were allocated to 5 groups in a randomized complete way with 2 pens per group and 3 pigs per pen. Supplementation of LA and 38W improved (p < 0.05) growth performance, intestinal pathogen bacteria count, fecal noxious odor and diarrhea incidence. In conclusion, supplementation of 38W strains isolated from white kimchi can act as probiotics by inhibiting E. coli and SE.

In order to make piglet diets more effective, it is necessary to investigate effective methods for breaking down xylan in cereal. The objective of this study was to determine the effects of dietary stimbiotic (STB) supplementation on growth performance, intestinal morphology, immune response and intestinal microbiota in weaned piglets. A total of 24 (Duroc × Yorkshire × Landrace) weaned pigs (initial body weight of 8.01 ± 0.38 kg and 28 ± 3 d old), were assigned to 4 treatments with 6 replicates per treatment. Pigs were housed in individual pens for 17 days, including 5 days adaption period and 12 days after the first Escherichia coli (E. coli) challenge. The experiment was conducted in a 2 × 2 factorial arrangement of treatments consisting of two levels of challenge (challenge and non-challenge) and two levels of STB (0 and 0.5 g/kg diet). Supplementations of STB 0.5 g/kg improved the gain to feed ratio (G:F) (P < 0.05) in piglets challenged with shiga toxigenic E. coli (STEC). STB supplementation decreased (P < 0.05) white blood cells, neutrophils, lymphocytes, and expression levels of tumor necrosis factor-alpha and interleukin-6. Supplementation of STB improved (P < 0.05) the lymphocytes and neutrophils in piglets challenged with STEC on 12 dpi. Supplementation of STB also improved (P < 0.05) the villus height to-crypt depth ratio of ileum in piglets challenged with STEC. Supplementation of STB increased (P < 0.05) the expression levels of claudin-1 of ileum. In genus level, supplementation of STB increased (P < 0.001) the abundance of Prevotella compared to non-supplementation of STB groups in pre-inoculation period. Also, supplementation of STB decreased (P < 0.05) the abundance of Faecalibacterium and Eubacterium_coprostanoligenes_group compared to non-supplementation of STB groups in post-inoculation period. In phylum level, supplementation of STB increased (P < 0.05) the abundance of Desulfobacterota and Fibrobacterota in pre-inoculation period. E. coli challenge increased the abundance of Fibrobacterota compared to non-challenged group in post-inoculation period. In conclusion, these findings indicated that STB supplementation could alleviate a decrease of the performance, immune response, and inflammatory response in piglets induced by the STEC challenge.

The scale of human accidents and the resultant damage has increased due to recent large-scale urban (building) fires, meaning there is a need to devise an effective strategy for urban disasters. In the event of a fire, it is difficult to evacuate in the early stages due to the loss of detection function, difficulty in securing visibility, and confusion over evacuation routes. Accordingly, for rapid evacuation and rescue, it is necessary to build a city-level fire safety service and digital system based on smart technology. In addition, both forest and building fires emit a large amount of carbon dioxide, which is the main cause of global warming. Therefore, we need to prepare both energy and fire management to achieve carbon neutrality by 2030. In this study, we developed an AI-based smart fire safety system for efficient urban integrated management using a city-based fire safety architecture. In addition, we designed a fire management infrastructure and an energy management system for buildings. The proposal was demonstrated by building a test bed in the A building, and the AR-based mobile/web application was tested for optimized evacuation management. Furthermore, AI-based fire detection and the optimal evacuation of occupants were implemented through deep learning-based fire information data analysis. As a result, this paper presents four points for safety and energy management, and we demonstrate that the optimization of occupant evacuation ability and energy saving can be achieved. We also analyze the efficiency of the data transfer rate to prevent data communication delays by using Virtual Edge Gateway (VEG) management. In the future, we expect that the appearance of future fire and energy management buildings through this research will produce more accurate data prediction technology and the development of cutting-edge smart technology in smart city infrastructures.

Solar power systems, such as photovoltaic (PV) systems, have become a necessary feature of zero-energy buildings because efficient building design and construction materials alone are not sufficient to meet the building’s energy consumption needs. However, solar power generation is subject to fluctuations based on weather conditions, and these fluctuations are higher than other renewable energy sources. This phenomenon has emphasized the importance of predicting solar power generation through weather forecasting. In this paper, an Automatic Machine Learning (AML)-based method is proposed to create multiple prediction models based on solar power generation and weather data. Then, the best model to predict daily solar power generation is selected from these models. The solar power generation data used in this study was obtained from an actual solar system installed in a zero-energy building, while the weather data was obtained from open data provided by the Korea Meteorological Administration. In addition, To verify the validity of the proposed method, an ideal data model with high accuracy but difficult to apply to the actual system and a comparison model with a relatively low accuracy but suitable for application to the actual system were created. The performance was compared with the model created by the proposed method. Based on the validation process, the proposed approach shows 5–10% higher prediction accuracies compared to the comparison model.

Energy prediction models and platforms are being developed to achieve carbon-neutral ESG, transition buildings to renewable energy, and supply sustainable energy to EV charging infrastructure. Despite numerous studies on machine learning (ML)-based prediction models for photovoltaic (PV) energy, integrating models with carbon emission analysis and an electric vehicle (EV) charging platform remains challenging. To overcome this, we propose a building-specific long short-term memory (LSTM) prediction model for PV energy supply. This model simulates the integration of EV charging platforms and offer solutions for carbon reduction. Integrating a PV energy prediction model within buildings and EV charging platforms using ICT is crucial to achieve renewable energy transition and carbon neutrality. The ML model uses data from various perspectives to derive operational strategies for energy supply to the grid. Additionally, simulations explore the integration of PV-EV charging infrastructure, EV charging control based on energy, and mechanisms for sharing energy, promoting eco-friendly charging. By comparing carbon emissions from fossil-fuel-based sources with PV energy sources, we analyze the reduction in carbon emission effects, providing a comprehensive understanding of carbon reduction and energy transition through energy prediction. In the future, we aim to secure economic viability in the building energy infrastructure market and establish a carbon-neutral city by providing a stable energy supply to buildings and EV charging infrastructure. Through ongoing research on specialized models tailored to the unique characteristics of energy domains within buildings, we aim to contribute to the resolution of inter-regional energy supply challenges and the achievement of carbon reduction.

To realize carbon neutrality, understanding the energy consumed in the building sector, which is more than that in other sectors, such as industry, agriculture, and commerce, is pivotal. Approximately 37% of energy consumption belongs to the building sector, and management of building energy is a critical factor. In this paper, we present an energy sharing scenario for energy stabilization, assuming that electric vehicles and their charging stations are widely distributed in the future. Consequently, fewer fuel cars will exist, and electric cars will become the major mode of transportation. Therefore, it is essential to install charging stations for electric vehicles in the parking lots of future buildings, and business models are expected to expand. In this paper, we introduce a future energy stabilization mechanism for peak power management in buildings and present a platform that entails connection-based energy trading technology based on a scenario. We also propose an energy supply strategy to prevent excess prices incurred due to peak consumption. Then, we analyzed the electricity bill for one month through scenario-based simulations of an existing building and the proposed system. When applying the proposed system, we derived a result that can reduce electricity rates by 38.3% (best case) to 78.5% (worst case) compared with the existing rates.

Cellulose is a glucose polymer and the most abundant biological material on earth. Because it is biodegradable and yet water insoluble, cellulose has been pursued in the past as a scaffold or base structural material for medical applications, sensors, and optical devices. Patterning of two cellulose polymers, cellulose acetate and cellulose acetate butyrate, by photoablative lithography at 172 nm has been demonstrated and is reported here. This 3D subtractive process yields complex micro- and nanostructures and optical components, including sinusoidal gratings and waveguides. Having a depth precision of 15 nm and requiring no photoresist or solvents, vacuum-ultraviolet photoetching of cellulose polymer films proceeds at a constant rate of ∼0.8 μm/h for depths of up to and beyond 25 μm when the intensity of the flat lamp is 10 mW cm−2. A polydimethylsiloxane (PDMS) microimprinting process, in which photoetched cellulose serves as a negative master mold for PDMS, provides feature sizes as small as 0.5 μm and allows for optical structures such as gratings to be integrated with microfluidic devices while eliminating the existing necessity of fabricating Si molds in a cleanroom environment.

Bitcoin is a decentralized digital currency that has gained significant attention and growth in recent years. Unlike traditional currencies, Bitcoin does not rely on a centralized authority to control the supply, distribution, and verification of the validity of transactions. Instead, Bitcoin relies on a peer-to-peer (P2P) network of volunteers to distribute pending transactions and confirmed blocks, to verify transactions, and to collectively implement a replicated ledger that everyone agrees on. This P2P network is at the heart of Bitcoin and many other blockchain technologies. In this paper, we present a comparative measurement study of nodes in the Bitcoin network. We measure and analyze how many the so-called “volunteers” are in the Bitcoin P2P network by scanning the live Bitcoin network for 37 days in 2018 and compare them with the data reported by prior work in 2013~2016. This paper is motivated by the fact that Bitcoin has experienced explosive growth in terms of a number of users, transactions, value, and interest over a recent couple of years. Our investigation includes the IP addresses of Bitcoin nodes, size of the network, power law in the geographic distribution, protocol, and client versions, and network latencies and shows how today's network is different from early days. In addition, based on the observations made from the measurement study, we propose a simple distance-based peer selection rule for improved connectivity and faster data propagation. The evaluation results show that our proposed lightweight and backward-compatible peer selection rule has the potential to reduce data dissemination latency.

PM014 (HL301) is a standardized herbal mixture derived from a traditional Korean medicine, Chung-Sang-Bo-Ha-Tang. Previously, we reported that PM014 treatment significantly suppressed pulmonary fibrosis, one of the frequent adverse effects of anticancer therapy in lung cancer. Before the clinical application of PM014 in anticancer therapy, the safety and efficacy of PM014 in combination with conventional anticancer drugs should be addressed to determine whether PM014 can be used in lung cancer. Lewis lung cancer–bearing mice were injected with 10 mg/kg of cisplatin or paclitaxel on day 5. Starting on day 7, the mice were administered 200 mg/kg PM014 every 2 days. On day 15, all mice were assessed by biochemical and histological analyses. PM014 did not block the antitumor activity of cisplatin and paclitaxel. Coadministration of PM014 and antitumor agents did not elevate the aspartate transaminase/alanine transaminase ratio or the blood urea nitrogen/creatinine ratio. Histopathological analysis also showed that PM014 did not induce hepatic or renal injury. Moreover, PM014 had no apparent inhibitory effects on drug metabolizing enzymes, indicating that PM014 did not alter the pharmacokinetics of chemotherapeutic drugs. Overall, these data show the safety and compatibility of combination therapy of PM014 and chemotherapies for the treatment of lung cancer.

Smart energy technologies, services, and business models are being developed to reduce energy consumption and emissions of CO2 and greenhouse gases and to build a sustainable environment. Renewable energy is being actively developed throughout the world, and many intelligent service models related to renewable energy are being proposed. One of the representative service models is the energy prosumer. Through energy trading, the demand for renewable energy and distributed power is efficiently managed, and insufficient energy is covered through energy transaction. Moreover, various incentives can be provided, such as reduced electricity bills. However, despite such a smart service, the energy prosumer model is difficult to expand into a practical business model for application in real life. This is because the production price of renewable energy is higher than that of the actual grid, and it is difficult to accurately set the selling price, restricting the formation of the actual market between sellers and consumers. To solve this problem, this paper proposes a small-scale energy transaction model between a seller and a buyer on a peer-to-peer (P2P) basis. This model employs a virtual prosumer management system that utilizes the existing grid and realizes the power system in real time without using an energy storage system (ESS). Thus, the profits of sellers and consumers of energy transactions are maximized with an improved return on investment (ROI), and an intelligent demand management system can be established.

Recent advances in nanomaterial preparation and printing technologies provide unique opportunities to develop flexible hybrid electronics (FHE) for various healthcare applications. Unlike the costly, multi-step, and error-prone cleanroom-based nano-microfabrication, the printing of nanomaterials offers advantages, including cost-effectiveness, high-throughput, reliability, and scalability. Here, this review summarizes the most up-to-date nanomaterials, methods of nanomaterial printing, and system integrations to fabricate advanced FHE in wearable and implantable applications. Detailed strategies to enhance the resolution, uniformity, flexibility, and durability of nanomaterial printing are summarized. We discuss the sensitivity, functionality, and performance of recently reported printed electronics with application areas in wearable sensors, prosthetics, and health monitoring implantable systems. Collectively, the main contribution of this paper is in the summary of the essential requirements of material properties, mechanisms for printed sensors, and electronics.

Currently, many intelligent building energy management systems (BEMSs) are emerging for saving energy in new and existing buildings and realizing a sustainable society worldwide. However, installing an intelligent BEMS in existing buildings does not realize an innovative and advanced society because it only involves simple equipment replacement (i.e., replacement of old equipment or LED (Light Emitting Diode) lamps) and energy savings based on a stand-alone system. Therefore, artificial intelligence (AI) is applied to a BEMS to implement intelligent energy optimization based on the latest ICT (Information and Communications Technologies) technology. AI can analyze energy usage data, predict future energy requirements, and establish an appropriate energy saving policy. In this paper, we present a dynamic heating, ventilation, and air conditioning (HVAC) scheduling method that collects, analyzes, and infers energy usage data to intelligently save energy in buildings based on reinforcement learning (RL). In this regard, a hotel is used as the testbed in this study. The proposed method collects, analyzes, and infers IoT data from a building to provide an energy saving policy to realize a futuristic HVAC (heating system) system based on RL. Through this process, a purpose-oriented energy saving methodology to achieve energy saving goals is proposed.

Decentralization and immutability characteristics of blockchain technology has attracted numerous blockchain-based systems and applications to be proposed. However, technical shortcomings such as low transaction speed, complexity, scalability, and vulnerability to certain attacks have been identified, making it challenging to use the technology on general consumer applications and services. To address the problem, we propose a new application service platform architecture called DDNB (Doubly Decentralized Network Blockchain). DDNB divides the system into multiple layers in order to take advantage of permissioned blockchain for its processing speed and security, while allowing permissionless open use of the system to application developers. To allow any node to freely participate in application services, DDNB adopts a novel periodic node self-verification process and query chaining mechanism to authenticate newly joining nodes and validate transactions effectively and efficiently. The proposed architecture is evaluated in terms of its processing speed and security on a real proof-of-concept prototype system.

Recently, fire accidents in buildings have become bigger around the world, and it has become necessary to build an efficient building disaster management system suitable for fires in a Smart City. As building fires increase the number of casualties and property damage, it is necessary to take appropriate action accordingly. There has been an increasing effort to develop such disaster management systems worldwide by applying information communication technology (ICT), and many studies have been conducted in practice. In this paper, an augmented reality (AR)-based Smart Building and Town Disaster Management System is suggested in order to acquire visibility and to grasp occupants in case of fire disasters in buildings. This system provides visualization information and optimal guide for quick initial response by utilizing smart element AR-based disaster management service through linkage of physical virtual domain in the building. Additionally, we show a scenario flow chart of the fire extinguishment process according to the time from the ignition stage to the extinguishment stage in the building. Finally, we introduce the related sensors, the actuators, and a small test-bed for AR-based disaster management service. This test-bed was designed for interlocking and interoperability test of the system between the sensors and the actuators. It is expected that the proposed system can provide a quick and safe rescue guideline to the occupants and rescuers in the building where fire is generated and in regions of poor visibility.

In the changing environment of the Internet of Things, optimal energy management in smart spaces requires intelligent and reliable energy-aware-based context sensing and technologies that are capable of recognizing and analyzing the big-data user pattern. In this article, we propose an intelligent and reliable standby power management system. The system uses physical and virtual user behavioral pattern analysis based on energy-aware management to cut-off the standby power of office appliances in the office environment. We propose a two-step priority power-aware method. The first step entails physical perception and management that controls devices through user recognition and device relationship scenarios. The second step is virtual perception and management that controls the standby power by collecting user behavioral patterns and performs an analysis based on a rule mechanism. The proposed system was applied to three locations (offices A, B, and C) in the university test-bed. Power consumption was reduced to 23% of the original consumption through the elimination of unnecessary standby power consumption.

In the coming Internet of Things era, billions of users and devices will be connected to the Internet; this will lead beyond the era of super-connection to the era of super-fusion. In this era, it is more important than ever to design a highly scalable Internet of Things infrastructure by mass customization for cost-effective production of exponentially increasing numbers of Internet of Things systems to provide more intelligent service in smart spaces. The purpose of this article is the design of mass-customization-based Internet of Things system through three-level analysis of the building; it proposes a new concept of a systematic design for providing economical Internet of Things systems for intelligent service in smart building spaces through three-level analysis comprising environmental-, service-, and functional-level analyses.

The development of the Internet of Things (IoT) technologies has enabled smart objects to communicate with each other, and various IoT methods and techniques have appeared accordingly. At this point in time, there is a growing need for big data-based energy-IoT technology that can reduce energy consumption. However, despite the emergence of these technologies for IoT, there is still a lack of control systems to surmount the energy efficiency problem of hyperconnected IoT applications. In this paper, we attempt to reduce energy consumption by automatically controlling the communication between each device by establishing three different energy-IoT-based chains regarding the relationship of connections between devices.

A smart grid (SG) has attracted great attention due to recent environmental problems. SG technologies enable users, such as energy system operators and consumers, to reduce energy consumption and the emission of greenhouse gases, by changing energy infrastructure more efficiently. As a part of the SG, home energy management system (HEMS) has become increasingly important, because energy consumption of a residential sector accounts for a significant amount of total energy consumption. However, a conventional HEMS has some architectural limitations on scalability, reusability, and interoperability. Furthermore, the cost of implementation of a HEMS is very expensive, which leads to the disturbance of the spread of a HEMS. Therefore, this paper proposes an Internet of Things- (IoT-) based HEMS with lightweight photovoltaic (PV) system over dynamic home area networks (DHANs), which enables the construction of a HEMS to be more scalable, reusable, and interoperable. We suggest the techniques for reducing the cost of the HEMS with various perspectives on system, network, and middleware architecture. We designed and implemented the proposed HEMS and conducted a experiment to verify the performance of the proposed system.

Owing to a paradigm shift toward Internet of Things (IoT), researches into IoT services have been conducted in a wide range of fields. As a major application field of IoT, waste management has become one such issue. The absence of efficient waste management has caused serious environmental problems and cost issues. Therefore, in this paper, an IoT-based smart garbage system (SGS) is proposed to reduce the amount of food waste. In an SGS, battery-based smart garbage bins (SGBs) exchange information with each other using wireless mesh networks, and a router and server collect and analyze the information for service provisioning. Furthermore, the SGS includes various IoT techniques considering user convenience and increases the battery lifetime through two types of energy-efficient operations of the SGBs: stand-alone operation and cooperation-based operation. The proposed SGS had been operated as a pilot project in Gangnam district, Seoul, Republic of Korea, for a one-year period. The experiment showed that the average amount of food waste could be reduced by 33%.