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Cross-layer approach in media access control (MAC) layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in wireless sensor network (WSN) and Internet of Things (IoT) applications. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes. Game theory optimization for distributed may increase the network performance. The purpose of this study is to survey the various operations that can be carried out using distributive and adaptive MAC protocol. Hill climbing distributed MAC does not need a central coordination system and location-based transmission with neighbor awareness reduces transmission power.

Distributed MAC in wireless networks is used to address the challenges like network lifetime, reduced energy consumption and for improving delay performance. In this paper, a survey is made on various cooperative communications in MAC protocols, optimization techniques used to improve MAC performance in various applications and mathematical approaches involved in game theory optimization for MAC protocol.

Spatial reuse of channel improved by 3%–29%, and multichannel improves throughput by 8% using distributed MAC protocol. Nash equilibrium is found to perform well, which focuses on energy utility in the network by individual players. Fuzzy logic improves channel selection by 17% and secondary users’ involvement by 8%. Cross-layer approach in MAC layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in WSN and IoT applications. Cross-layer and cooperative communication give energy savings of 27% and reduces hop distance by 4.7%. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes.

Other optimization techniques can be applied for WSN to analyze the performance.

Game theory optimization for distributed may increase the network performance. Optimal cuckoo search improves throughput by 90% and reduces delay by 91%. Stochastic approaches detect 80% attacks even in 90% malicious nodes.

Channel allocations in centralized or static manner must be based on traffic demands whether dynamic traffic or fluctuated traffic. Usage of multimedia devices also increased which in turn increased the demand for high throughput. Cochannel interference keep on changing or mitigations occur which can be handled by proper resource allocations. Network survival is by efficient usage of valid patis in the network by avoiding transmission failures and time slots’ effective usage.

Literature survey is carried out to find the methods which give better performance.

This study aims to apply for the first time in literature a new multi-objective sensor selection and placement optimization methodology based on the multi-objective Lichtenberg algorithm and test the sensors' configuration found in a delamination identification case study.

This work aims to study the damage identification in an aircraft wing using the Lichtenberg and multi-objective Lichtenberg algorithms. The former is used to identify damages, while the last is associated with feature selection techniques to perform the first sensor placement optimization (SPO) methodology with variable sensor number. It is applied aiming for the largest amount of information about using the most used modal metrics in the literature and the smallest sensor number at the same time.

The proposed method was not only able to find a sensor configuration for each sensor number and modal metric but also found one that had full accuracy in identifying delamination location and severity considering triaxial modal displacements and minimal sensor number for all wing sections.

This study demonstrates for the first time in the literature how the most used modal metrics vary with the sensor number for an aircraft wing using a new multi-objective sensor selection and placement optimization methodology based on the multi-objective Lichtenberg algorithm.

The Internet of Things has made the shift to the digital era possible, even though the Architecture, Engineering and Construction (AEC) sector has not embraced nor integrated it within the core functions compared to other sectors. The need to enhance sustainable construction with the adoption of Internet of Things in this sector cannot be overemphasized. However, the real-world applications of Internet of Things in smart buildings remain relatively unexplored in the AEC sector due to several issues related to deployment and energy-saving potentials. Given these challenges, this paper proposes to identify the present state of development and research in Internet of Things and smart buildings, identify Internet of Things clusters and applications in smart buildings.

Bibliometric analyses of papers from 2010 to 2023 using the Scopus database and scientometric evaluations using the VosViewer software were undertaken. The proper search keyword was identified by using the phrases “ Internet of Things” and “Smart Building”. A total of 1158 documents in all, written by 3540 different writers, representing 2285 different institutions from 97 different countries were looked at. A metasynthesis was conducted and a system of Internet of Things applications in a smart building is illustrated.

The development of IoT and Smart Buildings is done in two phases: initiation (2010–2012) and development phase (2013–2023). The IoT clusters comprised Internet of things, energy efficiency, intelligent buildings, smart buildings and automation; while the most commonly used applications were analysed and established. The study also determined the productive journals, documents, authors and countries.

Documents published in the Scopus database from 2010 to 2023 were considered for the bibliometric analysis. Journal articles, conference papers, reviews, books and book chapters written in English language represent the inclusion criteria, while articles in press, conference reviews, letters, editorials, undefined sources and all medical and health publications were excluded.

The results of this study will be used by construction stakeholders and policymakers to identify key themes and applications in IoT-enabled smart buildings and to guide future research in the policymaking process of asset management.

The study utilised bibliometric analysis, scientometrics and metasynthesis to investigate Internet of things applications in smart buildings. The study identified Internet of things clusters and applications for smart building design and construction.

This paper is a literature review on use of artificial intelligence (AI) among agricultural value chain (AVC) actors, and it brings out gaps in research in this area and provides directions for future research.

The authors systematically collected literature from several databases covering 25 years (1994–2020). They classified literature based on AVC actors present in different stages of AVC. The literature was analysed using Nvivo 12 (qualitative software) for descriptive and content analysis.

Fifty percent of the reviewed studies were empirical, and 35% were conceptual. The review showed that AI adoption in AVC could increase agriculture income, enhance competitiveness and reduce cost. Among the AVC stages, AI research related to agricultural processing and consumer sector was very low compared to input, production and quality testing. Most AVC actors widely used deep learning algorithm of artificial neural networks in various aspects such as water resource management, yield prediction, price/demand forecasting, energy efficiency, optimalization of fertilizer/pesticide usage, crop planning, personalized advisement and predicting consumer behaviour.

The authors have considered only AI in the AVC, AI use in any other sector and not related to value chain actors were not included in the study.

Earlier studies focussed on AI use in specific areas and actors in the AVC such as inputs, farming, processing, distribution and so on. There were no studies focussed on the entire AVC and the use of AI. This review has filled that literature gap.

At the present time, Industry 4.0 has proven its effectiveness and significance in automation and data exchange within industries across different sectors worldwide. In the current literature, there is still a lack of research on adopting Industry 4.0 in the manufacturing setting in developing economies. The main purpose of the present study is to explore the fundamental pillars and framework for ease of adoption of Industry 4.0 in manufacturing environments, along with highlighting the benefits and challenges.

In this study, a systematic literature review has been conducted through protocol, search, appraisal, synthesis, analysis, report (PSALSAR) model. In the literature, the articles are included within time span of 2008–2022, consisting keywords like Industry 4.0, blockchain, machine learning, artificial intelligence, Internet of Things, 3D printing, big data analytics, etc. Based on available literature, conceptual implementation framework of Industry 4.0 is proposed.

This study explored the key ingredients that play an essential role to bridge the gap and construct a strong relationship among physical and cyber world. The results reveals that the emerging technologies such as IoT, blockchain, artificial intelligence, augmented reality, 3D printing, big-data analytics, cloud-computing join hands to accomplish success in Industry 4.0 by reducing human interference for effective and efficient systems. In addition, the study also explored the possible benefits of emerging technologies with challenges faced by manufacturing setting during adaptation of Industry 4.0.

As per the authors' best knowledge, no research articles are found in literature which explore various emerging technologies in Industry 4.0 with its implementation framework in the manufacturing setting in developing economies. The main focus of the present study is to discover the literature review in defined area and find the research gap among current scenario and future trend for execution of Industry 4.0 in manufacturing environment.

Privacy preservation is a significant concern in Internet of Things (IoT)-enabled event-driven wireless sensor networks (WSNs). Low energy utilization in the event-driven system is essential if events do not happen. When events occur, IoT-enabled sensor network is required to deal with enormous traffic from the concentration of demand data delivery. This paper aims to explore an effective framework for safeguarding privacy at source in event-driven WSNs.

This paper discusses three algorithms in IoT-enabled event-driven WSNs: source location privacy for event detection (SLP_ED), chessboard alteration pattern (SLP_ED_CBA) and grid-based source location privacy (GB_SLP). Performance evaluation is done using simulation results and security analysis of the proposed scheme.

The sensors observe bound events or sensitive items within the network area in the field of interest. The open wireless channel lets an opponent search traffic designs, trace back and reach the start node or the event-detecting node. SLP_ED and SLP_ED_CBA provide better safety level results than dynamic shortest path scheme and energy-efficient source location privacy protection schemes. This paper discusses security analysis for the GB_SLP. Comparative analysis shows that the proposed scheme is more efficient on safety level than existing techniques.

The authors develop the privacy protection scheme in IoT-enabled event-driven WSNs. There are two categories of occurrences: nominal events and critical events. The choice of the route from source to sink relies on the two types of events: nominal or critical; the privacy level required for an event; and the energy consumption needed for the event. In addition, phantom node selection scheme is designed for source location privacy.

In a wireless sensor network (WSN), the sensor nodes are distributed in the network, and in general, they are linked through wireless intermediate to assemble physical data. The nodes drop their energy after a specific duration because they are battery-powered, which also reduces network lifetime. In addition, the routing process and cluster head (CH) selection process is the most significant one in WSN. Enhancing network lifetime through balancing path reliability is more challenging in WSN. This paper aims to devise a multihop routing technique with developed IIWEHO technique.

In this method, WSN nodes are simulated originally, and it is fed to the clustering process. Meanwhile, the CH is selected with low energy-based adaptive clustering model with hierarchy (LEACH) model. After CH selection, multipath routing is performed by developed improved invasive weed-based elephant herd optimization (IIWEHO) algorithm. In addition, the multipath routing is selected based on certain fitness functions like delay, energy, link quality and distance. However, the developed IIWEHO technique is the combination of IIWO method and EHO algorithm.

The performance of developed optimization method is estimated with different metrics, like distance, energy, delay and throughput and achieved improved performance for the proposed method.

This paper presents an effectual multihop routing method, named IIWEHO technique in WSN. The developed IIWEHO algorithm is newly devised by incorporating EHO and IIWO approaches. The fitness measures, which include intra- and inter-distance, delay, link quality, delay and consumption of energy, are considered in this model. The proposed model simulates the WSN nodes, and CH selection is done by the LEACH protocol. The suitable CH is chosen for transmitting data through base station from the source to destination. Here, the routing system is devised by a developed optimization technique. The selection of multipath routing is carried out using the developed IIWEHO technique. The developed optimization approach selects the multipath depending on various multi-objective functions.

This study reduces carbon emission in logistics distribution to realize the low-carbon site optimization for a cold chain logistics distribution center problem.

This study involves cooling, commodity damage and carbon emissions and establishes the site selection model of low-carbon cold chain logistics distribution center aiming at minimizing total cost, and grey wolf optimization algorithm is used to improve the artificial fish swarm algorithm to solve a cold chain logistics distribution center problem.

The optimization results and stability of the improved algorithm are significantly improved and compared with other intelligent algorithms. The result is confirmed to use the Beijing-Tianjin-Hebei region site selection. This study reduces composite cost of cold chain logistics and reduces damage to environment to provide a new idea for developing cold chain logistics.

This study contributes to propose an optimization model of low-carbon cold chain logistics site by considering various factors affecting cold chain products and converting carbon emissions into costs. Prior studies are lacking to take carbon emissions into account in the logistics process. The main trend of current economic development is low-carbon and the logistics distribution is an energy consumption and high carbon emissions.

Gas transmission pipelines are at constant risk of gas leakage or fire due to various atmospheric environments, corrosion on pipe metal surfaces and other external factors. This study aims to reduce the human and financial risks associated with gas transmission by regularly monitoring pipeline performance, controlling situations and preventing disasters.

Facility managers can monitor the status of gas transmission lines in real-time by integrating sensor information into a building information modeling (BIM) 3D model. Using the Monitoring Panel plugin, coded in C# programming language and operated through Navisworks software, the model provides up-to-date information on pipeline safety and performance.

By collecting project information on the BIM and installing critical sensors, this approach allows facility manager to observe the real-time safety status of gas pipelines. If any risks of gas leakage or accidents are identified by the sensors, the BIM model quickly shows the location of the incident, enabling facility managers to make the best decisions to reduce financial and life risks. This intelligent gas transmission pipeline approach changes traditional risk management and inspection methods, minimizing the risk of explosion and gas leakage in the environment.

This research distinguishes itself from related work by integrating sensor data into a BIM model for real-time monitoring and providing facility managers with up-to-date safety information. By leveraging intelligent gas transmission pipelines, the system enables quick identification and location of potential hazards, reducing financial and human risks associated with gas transmission.

Wireless sensor networks (WSN), as a solution for buried water pipe monitoring, face a new set of challenges compared to traditional application for above-ground infrastructure monitoring. One of the main challenges for underground WSN deployment is the limited range (less than 3 m) at which reliable wireless underground communication can be achieved using radio signal propagation through the soil. To overcome this challenge, the purpose of this paper is to investigate a new approach for wireless underground communication using acoustic signal propagation along a buried water pipe.

An acoustic communication system was developed based on the requirements of low cost (tens of pounds at most), low power supply capacity (in the order of 1 W-h) and miniature (centimetre scale) size for a wireless communication node. The developed system was further tested along a buried steel pipe in poorly graded SAND and a buried medium density polyethylene (MDPE) pipe in well graded SAND.

With predicted acoustic attenuation of 1.3 dB/m and 2.1 dB/m along the buried steel and MDPE pipes, respectively, reliable acoustic communication is possible up to 17 m for the buried steel pipe and 11 m for the buried MDPE pipe.

Although an important first step, more research is needed to validate the acoustic communication system along a wider water distribution pipe network.

This paper shows the possibility of achieving reliable wireless underground communication along a buried water pipe (especially non-metallic material ones) using low-frequency acoustic propagation along the pipe wall.