Abstract

In recent years artificial intelligence (AI) has been seen as a technology with tremendous potential for enabling companies to gain an operational and competitive advantage. However, despite the use of AI, businesses continue to face challenges and are unable to immediately realize performance gains. Furthermore, firms need to introduce robust AI systems and mitigate AI risks, which emphasizes the importance of creating suitable AI governance practices. This study, explores how AI governance is applied to promote the development of robust AI applications that do not introduce negative effects, based on a comparative case analysis of three firms in the energy sector. The study illustrates which practices are placed to produce knowledge that assists with decision making while at the same time overcoming barriers with recommended actions leading to desired outcomes. The study contributes by exploring the main dimensions relevant to AI’s governance in organizations and by uncovering the practices that underpin them.

Introduction

As businesses adopt Artificial Intelligence (AI), they are faced with new value propositions, but they also have to deal with new challenges, such as reducing the gap between intent and action(Amershi et al., 2019; Enholm et al., 2021; Mishra & Pani, 2020). Artificial intelligence has been perceived as a tool with which we can layer many different functions or as a solution to problems that are beyond the ability of traditional applications to solve. (Smuha, 2019). In order to gain a competitive advantage over their competitors (Raisch & Krakowski, 2021), businesses have implemented and deployed AI solutions to automate their processes, increase efficiency and reduce costs (Frank et al., 2019; Gregory et al., 2020). To achieve these goals, AI governance is essential. According to Butcher and Beridze (2019), AI governance “can be characterized as a variety of tools, solutions, and levers that influence AI development and applications”. Yet, further research is needed to better determine how AI Governance can be introduced into a company and whether AI governance can assist a company in achieving its objectives.

While AI has the potential to generate business value in terms of performance, productivity and effectiveness, it is not autonomous, as it works in concert with human capabilities (Zhang et al., 2021). Consequently, organizational capabilities are the results of combining and deploying multiple complementary resources within a firm to achieve competitive advantage (Mikalef & Gupta, 2021). When a firm optimizes its firm-level resources and adopts AI technological innovations, it can enhance its transformed projects’ business value which drives business value and impacts performance (Wamba-Taguimdje et al., 2020). Simultaneously, the AI algorithms can be considered performative in the sense that they assist in decision-making, the extent to which their use can form organizational processes, or even take autonomous decisions (Faraj et al., 2018; Grønsund & Aanestad, 2020) that leads to new organization capabilities through AI. The use of AI, for instance, could create more substantial customer acquisition or higher customer lifetime value and lower operating costs or reduce credit risk.

Discussion

In this study, we set out to explore the underlying activities that comprise an organization’s AI governance. Specifcally, we built on the prior distinction between structural, relational, and procedural dimensions of governance in order to understand how organizations are planning around their AI deployments. Through a multi-case study of three organizations that have been using AI for several years, we conducted a series of interviews with key respondents and identifed a set of activities that were relevant under each of the three dimensions, as well as challenges they faced during deployments of AI and how they managed to overcome them. Our analysis essentially points out the various obstacles that AI governance is oriented to overcoming, and the mechanisms employed to operationalize them.

Specifcally, we fnd that the obstacles that are identifed during the process of deploying AI are observable at diferent phases and concern diferent job roles. When it comes to difcult management responsibilities that a business owner must do, AI solutions can always provide a variety of responses and probabilities for each of these alternatives. However, AI lacks the ability to make decisions in specifc contexts. To make the ultimate decision, a business owner or manager must employ intuition to reconcile the choices provided by AI (Kar & Kushwaha, 2021). In addition, they span various levels of analysis, from the personal, such as fear of AI and reluctance of employees to adopt it, to organizational-level ones, such as organizational directives on how to comply with laws and regulations. What is more, the study reveals not only that AI governance is a multi-faceted issue for organizations but that it spans multiple levels, therefore requiring a structured approach when it is deployed. In addition, different concerns emerge at diferent phases of AI projects, so AI governance also encapsulates a temporal angle in its formation and deployment.

Abstract

     A quad-element multiple-input-multiple-output (MIMO) antenna with fractional bandwidth (FBW) of 52.42% (3.35–5.73 GHz) is proposed for LTE, WLAN (4.9/5 GHz), and 5G (sub-6 GHz) applications. The bandwidth is improved by introducing a tapered feed line and rectangular stubs in the partial ground plane. The maximum isolation of the proposed MIMO antenna is 27 dB. The diversity performance characteristics of the proposed antenna are studied in terms of the envelope correlation coefficient (ECC), diversity gain (DG), mean effective gain (MEG), total active reflection coefficient (TARC), isolation between the ports, and channel capacity loss (CCL) and the values obtained are 0.003, 9.98 dB, ±3 dB, −4 dB, −10 dB, and 0.10 bits/s/Hz respectively. A model of the proposed antenna is fabricated on the FR-4 substrate having a dielectric constant of 4.4 and a loss tangent of 0.02 with an electrical dimension of 0.45λ0 × 0.45λ0. The measured results demonstrate a decent likeness to simulated ones in the entire operating frequency range.

Introduction

     The current scenario for mobile communication is to achieve a higher data rate, capacity, low latency, and high resolution. The fifth-generation (5G) mobile communication has been deployed around the world to fulfill the above advantage [1,2]. It has been shown [3,4] that to improve the information throughput in a multipath environment for 5G operations, the MIMO antenna system should be adopted. MIMO antenna systems should have a minimal inter-element distance, low correlation values, and better isolation between inter elements [5]. The primary advantage of adopting an MIMO network over a normal one is that it can enhance wireless connection capacity while consuming less spectrum. The system’s link dependability and data rate can be enhanced by increasing the number of antennas on the transmitter/receiver, which results in more signal routes and thus higher performance. Hence MIMO techniques become very vital for wireless communication systems which are suffering from frequency constraints [6,7].

Conclusion

     A compact quad-element MIMO antenna of 40 × 40 × 1.6 mm3 for 5G, LTE, and WLAN frequency bands is designed, fabricated, and measured. The measured results demonstrate a decent likeness to simulated ones in the whole frequency range. The proposed design’s performance was evaluated and described in terms of impedance bandwidth, surface current distribution, reflection coefficient, gain, efficiency, and radiation characteristics. The MIMO provides good diversity performance with a low envelope correlation coefficient and a better diversity gain. Furthermore, within the operating frequency band, the proposed antenna obtained a maximum channel capacity of > 20 bits/s/Hz. The antenna has a total efficiency of 85.12% and a peak gain of 2.74 dBi. As a result, it is recommended as a candidate for 5G, WLAN, and LTE applications.

Abstract

     The emergence of the Industry 4.0 revolution to upgrade the Internet of Things (IoT) standards provides the prominence outcomes for the future wireless communication systems called 5G. The development of 5G green communication systems suffers from the various challenges to fulfill the requirement of higher user capacity, network speed, minimum cost, and reduced resource consumption. The use of 5G standards for Industry 4.0 applications will increase data rate performance and connected device’s reliability. Since the arrival of novel Covid-19 disease, there is a higher demand for smart healthcare systems worldwide. However, designing the 5G communication systems has the research challenges like optimum resource utilization, mobility management, cost-efficiency, interference management, spectral efficiency, etc. The rapid development of Artificial Intelligence (AI) across the different formats brings performance enhancement compared to conventional techniques. Therefore, introducing the AI into 5G standards will optimize the performances further considering the various end-user applications. We first present the survey of the terms like 5G standard, Industry 4.0, and some recent works for future wireless communications. The purpose is to explore the current research problems using the 5G technology. We further propose the novel architecture for smart healthcare systems using the 5G and Industry 4.0 standards. We design and implement that proposed model using the Network Simulator (NS2) to investigate the current 5G methods. The simulation results show that current 5G methods for resource management and interference management suffer from the challenges like performance trade-offs.

Introduction

     The further progress of the Internet of Things (IoT) reveals it is a fundamental piece of different applications, for instance, keen home, smart healthcare, savvy agriculture, brilliant city, and so forth. The remarkable improvement of IoT devices encounters accepting various benchmarks and progressions. Another significant issue in IoT gadgets is interoperability among particular gadgets and organizations. The specific devices should be versatile in accepting the situation in passing on information with less human commitment (Xu et al. 2004). The human free and human-driven are two kinds of unavoidable perspectives on account of human affiliation. The energy effectiveness and resource management in IoT acquired huge examination interests. The key necessity of IoT empowered WSNs is that they ought to work steadily and economically for a more drawn-out period with no requirement for human mediation (He et al. 2004). Devices in such IoT systems will ordinarily work dependent on battery power sources, and subsequently, energy proficiency has normally of most extreme significance in a gadget the executives (Nadeem et al. 2015; Arifin and Ohtsuki 2014). Thinking about the WSN area, energy productivity for battery worked sensor hubs and lifetime upgrades have been researched issues for a long time (Riggio and Sicari 2009; Sohrabi et al. 2000). Medium Access Control (MAC) layer conventions center around changing the obligation cycle for sensor hubs and steering layer conventions have intended for information accumulation and many-to-one transmission. Likewise, since IoT gadgets working in the IoT arrange worldview are additionally battery worked, battery utilization ought to be remembered during IoT organize organization. The acknowledgment of cost decreases to accomplish green systems administration is the exploration goal of this research. Numerous energy productive plans for WSN have been proposed in the ongoing past, for example, a chain of command (Sohrabi et al. 2000) and careful (Mikhail et al. 2017a, b) ones, anyway there are numerous gaps identified with effective information total and spread strategies.

Conclusion and future work

     Progressions in the 5G standard and its integration with emerging Industry 4.0 and AI innovations were studied in this paper. The fast-expanding savvy devices and IoT modules in volume produce a huge measure of information traffic, putting extra weight on existing portable remote sensor networks. This paper presents an itemized review on the combination of 5G, Massive MIMO, and AI for improving IoT performance. The wide range of recent studies reviewed throughout this paper and based on it the research gaps for future roadmap discussed. We further have designed the novel model for smart healthcare monitoring using the methods of 5G and IoT together. The model was implemented and evaluated using the recent 5G methods for resource and interference management. The simulation results reveal the research gaps for further development.

Abstract

     Small- and medium-sized enterprises (SMEs) play a crucial role within a country’s economy considering that they provide a source of skills and innovation for entrepreneurship and their capacity for introducing, integrating and disseminating new technologies is incomparable. However, the world may be looking at an impending devastating recession delivered by the coronavirus pandemic. As governments intensify restrictions on business to halt the spread of the pandemic, the fear of the virus also reconfigures the very concept of business and the workplace. Therefore, there is a need for a greater focus on digital transformation considering that physical distancing requirements to curb the spread of this virus may become a cultural orientation for businesses and the workplace. A real digital transition is anticipated for small businesses with the 5G network technology. 5G network will not just be a technological connection but will affect different socio-economic sectors and will stimulate innovation in small companies. The goal of this paper was to carry out a literature review on the potential ways small businesses can leverage on 5G network for digital innovation. The paper proposed that small and medium businesses can leverage the 5G Mobile Technology through enhanced interpersonal communication, expanded remote work opportunities, innovative digital tools and supply chain efficiency. Finally, while many individuals and small business owners will profit from 5G technology some will work to undermine it. As a result, companies must keep this in mind when implementing 5G, or other new technology, and adjust their security protocols accordingly to remain secure.

Introduction

     Small businesses can expect a true digital transition with 5G (fifth generation of broadband data-networking digital communications technology) network technology (Tullberg et al., 2016). With an estimated annual growth rate of 97% and approximately 40% of the global population using IoT apps on a 5G network, the new mobile technology has the potential to generate a $251 trillion economic impact by 2025. This growth can be attributed to the fact that the 5G network will not only provide a technological connection but will also have an impact on various socioeconomic sectors and encourage small business innovation (Webb, 2016). The new technological link will make it possible to implement well-known initiatives, such as Smart City, Smart Company, and artificial intelligence in business (Zhu et al., 2016). Because of increased data transfer speed and reduced time between signal transmission and reception, the 5G network will redefine the role of connectivity and connections in global society, providing a new foundation for business innovation, particularly in small businesses. The goal of this paper is to conduct a review of the literature on the various ways small businesses can use the 5G network for digital innovation.

Conclusion

     The goal of this article was to establish a link between 5G technology and digital innovation, particularly in SMEs. The article began by establishing the context of the paper by summarising current knowledge and background information on the subject. This was accomplished by stating the purpose of the paper, the research question/problem, briefly explaining the methodological approach, and emphasising the study’s potential outcomes. Conceptual framework and synthesis were created to demonstrate the key relationships between the focal constructs (5G technology and digital innovation). This was done to aid comprehension of the conceptual framework. This paper contends that the implementation of 5G technology creates a platform for digital innovation in SMEs’ communication, remote working, supply chains, and marketing activities. This can simplify and improve the efficiency of work processes and operations within SMEs, resulting in increased productivity. 5G technology will create enormous opportunities for new revenue streams and will serve as the foundation for business innovation and development on a scale that companies in almost every industry have yet to fully explore.

Abstract

     An individual’s health is one of the essential aspects of life, but due to the limited technology at health care centers, many people face various restrictions during their treatment. These days, Internet-of-Things (IoT) is the most fascinating topic that provides solutions to these limitations in various ways. The IoT is utilized in various healthcare conducts that include detection, treatment, and monitoring of diseases. Wearable devices are a part of IoT that is proposed for helping patients to get the correct treatment. The conventional communication networks developed for humans-based applications face many issues like stringent latency, restricted computing capability, and short battery life. On the other hand, the onset of 5G has developed a new set of technologies that offer the vital “backbone” for connecting to the billions of devices for the upcoming IoT that would completely modify our professional and private lives. Due to the data capabilities, intelligent management, and superfast connectivity of 5G, this network has enabled new health care opportunities that include treatment, data analytics, diagnostics, and imaging. In the current review, a systematic literature survey of IoT, IoT-based wearable devices, and the role of 5G in IoT for healthcare is described in detail. Furthermore, we have explained the usage of wearable devices in detecting the issue in terms of healthcare, such as curing, monitoring, and detection of disease. Nevertheless, this review article also emphasizes the employment of IoT architecture and its wearable devices in addition to the upcoming research challenges related to this area.

Introduction

     With the increase in the advancement of technology, the demand for comfort and accessibility is also increasing, leading to an increase in the development of funding programs. Usually, it has been observed that many city hospitals lack to fulfil certain medical requirements of the patients, and therefore, patients have to search in other cities/move to other countries’ hospitals to complete their desired medical needs (Surantha et al., 2021). These days, the Internet-of-Things (IoT) in healthcare has become one of the latest trending subjects and has been found as a promising characteristic to improve the current technologies that lower its cost in each aspect of healthcare. Moreover, the IoT in biomedical is considered as the need of an hour that is required to provide medical aid to humans for monitoring, managing, detecting, and taking action from the system after receiving data, thereby effectively reducing the cost of health expenses (Khan et al., 2018). IoT is the sub-category of a computer having sensors, microcontrollers, and transceivers that are interconnected to provide information to aid the user with detailed information. It is applied in various healthcare means, including detection of disease as a precaution, monitoring disease as a self-healing route, and treating disease as the healing solution (YIN et al., 2016). Wearable devices are a part of IoT that have been developed for helping people to get the correct treatment. The IoT-based wearables are smart devices that could be worn with external accessories, tattooed or even adhered on the skin, implanted in the body, or embedded in garments and clothing.

Conclusion and prospects

     With the advancement in science and technology, the accessibility of healthcare has now become easy and affordable. But, many city hospitals lack the desired medical requirements, and therefore, the introduction of biosensors has eased these problems. Moreover, these days, the Internet-of-Things (IoT) in healthcare has become one of the latest trending subjects and a promising characteristic to improve the current technologies that lower its cost in each aspect of healthcare. IoT has become the need of the hour as it is useful for monitoring, managing, detecting, and taking action from the system after receiving data, thereby effectively reducing the excess cost of health expenses. Wearable devices are a part of IoT that have been developed to help patients get the correct treatment. These IoT-based wearables devices are considered smart devices that could be worn with external accessories tattooed or even adhered to on the skin, implanted in the body, or embedded in garments and clothing. These smart devices can link with the internet for collecting, sending data, and receiving information for making smart decisions. These wearables have become a vital fragment of IoT technology, and their growth is shifting towards more specialized and practical utility from simple accessories.

Abstract

     The rollout of 5G wireless service has been much anticipated by consumers across the U.S. since it will bring faster data download speeds and expanded service; however, the impact to aviation and air travel are as a major issue and the potential impact to aviation has not been estimated or assessed. This paper fills that gap and provides the first analysis of the potential number of flights impacted by 5G at ten of the busiest airports in the U.S. Using detailed historical weather and flight data in 2019 at 10 large hub airports, we find that nearly 15,700 flight arrivals could be directly impacted annually, at the ten airports considered. The geographical and seasonal impact varies significantly with more flights affected by the potential for 5G interference at airports in Seattle and Dallas Fort-Worth and relatively few flights affected at airports in Phoenix and Las Vegas. A case study examining ten years of data at Chicago O’Hare International, a hub for two major airlines, suggests that over 2,400 flights every year could be impacted by 5G interference. Fortunately, there has been increasing cooperation between the cell phone industry and aviation stakeholders to ensure a safe rollout of 5G C-band; this paper provides a significant contribution by documenting the issues and context for aviation operations.

Introduction

     The rollout of 5G wireless service has been much anticipated by consumers across the U.S. as data download speeds will be increased and service expanded. 5G C-band enables data intensive technology for personal and business use, ranging from entertainment such as video games to critical communications for public services (Pham et al, 2020), and provides more consistent, faster speeds and increased capacity. The communications band or “C” band was originally designated for industrial applications and satellite communications and were repurposed for 5G wireless between 3.7 and 3.98 GHz. C-band is one component of the mid-band frequency between 3.3 and 4.2 GHz. The benefits of the new 5G C-band service have been contraindicated near airports by the aviation industry due to the potential for negative operational and safety impacts. Since the 5G C-band frequencies is very close to the Aeronautical Radionavigation Service (ARS) spectrum (as shown in Fig. 1), there is a potential for signal interference which could potentially disrupt the operation of the radio/radar altimeter equipment on many transport aircraft. This equipment is necessary to conduct certain low visibility procedures when weather conditions do not permit use of standard precision or non-precision procedures. The inability of aircraft to safely perform these procedures could generate flight disruptions throughout the system. This fact was underscored by the acknowledgement that over 100 pilot reports of potential 5G interference have been made in the first few weeks of 5G rollout (Levin and Shields, 2022). Additionally, the U.S. Transportation Secretary noted that these issues will not be fixed by the summer flying season (Reardon, 2022).

Conclusions

     As the U.S. and other countries introduce 5G C-band, the need to understand the potential disruption to air travel is apparent. This paper provides the first estimates of the number of flights that could be potentially impacted at ten of the busiest airports in the U.S. These flights conducting low visibility procedures could be delayed, diverted, or cancelled. The number of flights conducting these low visibility approaches varies across seasons and location. Some airports, such as Seattle-Tacoma International could experience a significant impact to flight operations while others such as Harry Reid International in Las Vegas could be minimally impacted. Dallas Fort-Worth International, which area serves as several major airline hubs and headquarters, experiences numerous low visibility flight operations with the greatest monthly variation. The systemic impact from disruptions out of these ten busy hub airports presents a significant risk to travelers and airline operations. These risks include delays and cancelations as well as their direct and indirect economic costs. Further, to highlight the significant potential impact we determined that Chicago O’Hare International had over 27,000 flights conduct low visibility operations in the decade from 2009 to 2019.

Abstract

     The expedite to network economy during the COVID-19 pandemic has raised the question of how to induce and sustain a societal and industrial transformation towards a more networked world. Among the driving forces behind network economy, the commercialization of 5G, the fifth generation of mobile technologies, is especially noteworthy. How does 5G induce such a transition? How do countries respond? are questions deserving more investigation. However, most discussions of 5G have been confined to standardization or standard-setting. To take into accounts interactions between technology and economy, we adopt Geels’ (2002) multi-level perspective to put 5G transition in the social-technical context. We choose China as an influential case and deploy mixed methods to analyze a variety of data sources. The results show a rich picture of technological transition, including: 1) 5G standard-setting as a transition trigger in the global level; 2) IoT incubation in the niche level; and 3) regime configuration in the national level. We help transcend the limitation of standardization studies, extend the scope of transition studies into network economy, and introduce more industrial dynamics.

Introduction

     The expedite to network economy during the COVID-19 pandemic has raised the question of how to induce and sustain a societal and industrial transformation towards a more networked world. Network economy is not a new thing since the world has been deeply embedded in a fabric interwoven by network infrastructure (Zammuto et al., 2007). What is new is that the pandemic has triggered transformations not only in a global scale, but also in a massive scope on every aspect of political, economic and social life. We have seen the rise of pandemic information systems, the move to on-line education, the increase in flexible work arrangements, and the intensification of network economy across many sectors (Whitelaw et al., 2020). The pandemic will end eventually, but the momentum it generated might have long-lasting effects. Network economy will continue making new ways of organizing and working possible (Brynjolfsson and McAfee, 2014), connecting humans and machines via a vast array of internet of things (IoT) applications (Shafique et al., 2020), and incorporating artificial intelligence (AI) as a component to augment and automate increasingly more functions and processes within as well as across organizations (Kellogg et al., 2020). It is therefore foreseeable a transition towards a more networked economy and society.

Conclusion and discussion

     Through the case study, we analyze changes in the three levels during 5G transition, which suggest: 1) 5G standard-setting as a transition trigger in the global level; 2) IoT incubation in the niche level; and 3) regime reconfiguration in the national level. These changes, however, must be put under the scrutiny of alignment to make linkages between them. According to Kemp et al. (2001), “It is the alignment of developments (successful processes within the niche reinforced by changes at regime level and at the level of the sociotechnical landscape) which determine if a regime shift will occur”. The alignment is important for stability and sustainability of both regime reconfiguration and actors’ construction and response. Therefore, we can observe how this alignment helps reinforce regime reconfiguration and stabilize a new regime.

Abstract

     Physical layer security (PLS) in Internet-of-Things (IoT) has attracted great attention in recent years. As an important and intrinsic property in an IoT system, node mobility is not fully investigated when designing a PLS scheme. Existing PLS works with mobility are designed with typical random mobile models, which cannot represent a real scenario. Considering this challenge, we propose a friendly jamming handover scheme to protect the downlink transmission from a controller to an actuator, with the help of multiple cooperative jammers to fight against a mobile conscious eavesdropper. In particular, we first introduce a conscious eavesdropping model (CEM) to characterize a real mobile wiretapping scenario. Second, we present a handover scheme to enhance security in a mobile scenario and then define handover efficiency to discuss the handover performance. Finally, numerical results are provided to verify the effectiveness of the proposed handover scheme, which demonstrates that our scheme can efficiently fight against a conscious mobile eavesdropper.

Introduction

     Internet of Things (IoT) is expected as a promising technique to achieve ubiquitous connectivity and intelligent information processing for the intelligent future life [1, 2]. Since the IoT is penetrating our daily life, the security and privacy are of the utmost importance [3–5]. Physical layer security (PLS) techniques have been attracted growing interests for the scenarios with resource-constrained IoT sensors and actuators [6–8]. A PLS scheme taking advantage of the unique properties of wireless channels can guarantee the information-theoretic communication security, regardless of the computing capability of eavesdroppers [9]. Various PLS schemes have been investigated to enhance secrecy in IoT networks, including multi-antenna beamforming and precoding [10, 11], artificial noise (AN) [12], intermittent cooperative jamming [13], and sociability-enabled PLS [8, 14, 15].

Conclusion

     This work investigated secure downlink transmmission in an IoT system with a mobile eavesdropper, and proposed a handover scheme to enhance PLS with the help of multiple cooperative jammers. In order to reflect the real situation, the conscious eavesdropping model was proposed to compare with the typical RWP model. Moreover, we introduced a metric called handover efficiency to reflect the handover performance. The numerical results verified that the handover scheme could efficiently improve the secrecy performance and effectively confront the conscious eavesdropper. The proposed scheme is feasible to provide security enhancement in many real mobile eavesdropping scenarios.

1- Introduction

2- Method

3- Experiment

4- Results

5- Discussion

6- Conclusion

References

Abstract

With the realization of the Internet of Things from theory to practical application, the work of ensuring high reliability of the system has become the key to system design, and it is also the obstacle to further promotion of the Internet of Things. This paper makes an in-depth study on the Internet of Things transmission and network reliability in complex environments. In this paper, we use the artificial bee colony algorithm to get the shortest path analysis of each cluster head node. The simulation results show that the algorithm proposed in this paper can effectively reduce the amount of data transmitted to sink by the sensor nodes through cluster head node fusion, improve the efficiency of data collection, energy consumption balance and network reliability, and extend the network life cycle. In addition, the index model of Internet of things reliability index system is established, and the comprehensive evaluation method of using the index is explained. The simulation results show that the proposed algorithm reduces the amount of data transmission and network energy consumption, prolongs the network life cycle, improves the efficiency of data fusion and data transmission reliability. Aodv-sms (abc-pso) routing recovery protocol shows that compared with other routing recovery strategies, packet transmission delay time is less, and the gap between them is more and more large; aiming at the end-to-end reliability and the network capacity, the paper focuses on the analysis of the impact of the change of communication link on the network capacity under the mobile node.

Introduction

In recent years, the scale of the network has expanded from one laboratory to one building to one, and there has been a strong thing. The Internet of Things system are also exposed: the working environment of the Internet of Things system is complex, and the stability of the communication link is lacking. The Internet of Things terminals are widely distributed, facing the shortcomings of terminal functions and vulnerable to attack. At this stage, it is the initial stage of the development of Internet of Things at home and abroad. The main research hotspots of many research teams focus on the following aspects: the formulation of relevant standards, the breakthrough of key technologies, and the exploration of commercial applications. Razzaque MA [1] proposed that the Internet of Things (IoT) envisions a future in which digital and physical objects or objects (eg, smartphones, televisions, cars) can be connected through appropriate information and communication technologies to achieve a range of applications. Perera C [2] surveyed more than 100 IoT smart solutions on the market and studied them carefully to determine the technologies, functions and applications used. Bertino E [3] found that based on a general description of the smart home management model of the overall framework, Stojkoska B L R [4] discusses current and future challenges of IoT-based solutions. Perera C [5] studied a variety of popular and innovative IoT solutions, using a framework built around well-known context-aware computing theory to evaluate these IoT solutions. Wang Yunan [6] realized the data recovery by using the data model of the IoT wireless sensor network with time-space correlation to perform the sparse sampling and matrix-filled approximate reconstruction techniques of the matrix composed of data samples. Xue Yuanfei [7] explored the application and design of intelligent vehicle management system for Internet of Things technology through the existing problems in the intelligent management of vehicles and the analysis of requirements.

1- Introduction

2- Material and methods

3- Sample

4- Results

5- Discussion

6- Conclusion

References

Abstract

To provide a diverse comprehension of teachers’ TPACK (Technological, Pedagogical, and Content Knowledge) and how TPACK is reflected in practice, this study examined teacher educators’ (TEs’) conceptions of technology integration. Specifically, the main objective of the study was to investigate the factors influencing Nigerian teacher educators’ technology integration using a self-completion survey administered to Nigerian teacher educators from three schools in the southern region of Nigeria. We utilized the partial least squares structural equation modeling (PLS-SEM) approach for the data analysis. Two frameworks—TPACK and Second Information Technology in Education Study (SITES)— guided the scale development. The results indicated that three constructs (perceived technological knowledge, teachers’ knowledge [excluding technology] and perceived knowledge for integrating technology) directly influenced the TEs’ technology integration, while two others (information and communication technology [ICT] pedagogical practices and perceived effect on students) did not. Among the teachers’ characteristics, teaching experience, and class size were found statistically associated with their technology integration. The results of this study are beneficial for developing professional training to help teachers integrate technology specifically by developing their ICT pedagogical practices. Through such training, teachers could be enlightened on how to align their perceived effect of teaching with technology.

Introduction

Both educators and policymakers have high expectations that ICT will support educational reforms and better teaching and learning practices (Elstad, 2016). In addition, ICT literacy and twenty-first century skills have been recognized as essential for productivity in an information society (Groff, 2013). Accordingly, what happens inside the classroom is crucial (OECD, 2016) and questions concerning how teacher trainees learn to integrate technology into their teaching practices should be considered. Nevertheless, it behooves TEs to help teacher trainees to become digitally literate individuals who can teach the necessary skills to their future students (Binkley et al., 2012; Howells, 2018); hence, TEs are recognized as “gatekeepers” (Tondeur et al., 2019), because of the role they play in the preparation of the future generation of teachers.

1. Introduction

2. Methodology

3. Implementation

4. Results

5. Conclusions and recommendations

Acknowledgments

Appendix A. Supplementary material

References

Abstract

Currently, there are both methodological and practical barriers that together preclude the use of theoretically sound approaches for network screening as part of a traffic safety management process. Methodological barriers include, among others, lack of a comprehensive framework for corridor-level network screening. Existing corridor screening methodologies use observed crash frequency as a performance measure. In practice, corridorlevel screening is extremely important because traffic safety engineers prefer to deploy countermeasures and provide homogenous conditions throughout corridors to meet drivers’ expectations and avoid confusion. On the other hand, practical barriers that limit the use of sound approaches for traffic safety include (1) significant data integration requirements, (2) a particular data schema is needed to enable analysis using specialized software, (3) time-consuming and intensive processes are involved, (4) substantial technical knowledge is needed, (5) visualization capabilities are limited, and (6) coordination across various data owners is required. This research proposes a systematic methodology for corridor-level network screening. The solution algorithm is implemented within a Business Intelligence (BI) platform to address, to the extent possible, the practical barriers listed above. BI provides methods and mechanisms to integrate and process data, generate advanced analytics, and visualize results by using intuitive and interactive web-based dashboards and maps. Experiments and results illustrate the advantage of using the proposed framework for corridor-level network screening implemented within a BI platform.

Introduction

Ensuring traffic safety is the focus of such federal legislation as the Transportation Equity Act for the 21st Century (TEA-21), the Safe Accountable Flexible and Efficient Transportation Equity Act – A Legacy for Users (SAFETEA-LU), and the Moving Ahead for Progress in the 21st Century (MAP-21). SAFETEA-LU and MAP-21 both require that states develop comprehensive Highway Safety Improvement Plans (HSIPs) (FHWA, 2013). One of the critical programs of HSIPs is the traffic safety management process, which involves annual reporting of the highway locations that exhibit the most severe traffic safety needs. By identifying the most hazardous roadway site locations, specific countermeasures can be implemented to improve safety conditions. In a traffic safety management process, identifying locations with the potential for safety improvements is known as network screening. Network screening is critical because a detailed engineering study for all network sites is expensive. The purpose of network screening is to review the entire roadway network, or portions, and identify and prioritize corridors and sites with potential for safety improvements. These identified corridors are recommended for further investigation and a detailed safety engineering study.

For network screening, despite the availability of approaches such as the Empirical Bayes (EB) method recommended by the Highway Safety Manual (HSM) (AASHTO, 2010) and those that deal with unobserved heterogeneity (Mannering et al., 2016; Mannering, 2018), practitioners continue using very simplistic methodologies which rely only on observed crash frequency or crash rates. For HSIP reports submitted to the Federal Highway Administration in fiscal year 2014, only four states used the EB for network screening as described in the HSM (FHWA, 2015).