Igbafe Orikumhi

Bio: Igbafe Orikumhi is an academic researcher from Hanyang University. The author has contributed to research in topics: Relay & Base station. The author has an hindex of 5, co-authored 21 publications receiving 494 citations. Previous affiliations of Igbafe Orikumhi include Universiti Teknologi Malaysia.

An Overview of Internet of Things (IoT) and Data Analytics in Agriculture: Benefits and Challenges

Abstract: The surge in global population is compelling a shift toward smart agriculture practices. This coupled with the diminishing natural resources, limited availability of arable land, increase in unpredictable weather conditions makes food security a major concern for most countries. As a result, the use of Internet of Things (IoT) and data analytics (DA) are employed to enhance the operational efficiency and productivity in the agriculture sector. There is a paradigm shift from use of wireless sensor network (WSN) as a major driver of smart agriculture to the use of IoT and DA. The IoT integrates several existing technologies, such as WSN, radio frequency identification, cloud computing, middleware systems, and end-user applications. In this paper, several benefits and challenges of IoT have been identified. We present the IoT ecosystem and how the combination of IoT and DA is enabling smart agriculture. Furthermore, we provide future trends and opportunities which are categorized into technological innovations, application scenarios, business, and marketability.

Enabling smart agriculture in Nigeria: Application of IoT and data analytics

Abstract: The Nigeria agriculture sector is receiving a lot of attention in recent years due to the need to diversify its economy. Two key gaps facing the agriculture sector have been identified. They include the inability to meet domestic food requirements and the inability to export at quality levels required for market success. We envisage that these problems can be solved by using internet of things (IoT) and data analytics (DA). In this paper, the application of IoT technologies and DA in agriculture are discussed. The benefits and challenges of deploying the IoT and DA are presented. Finally, methods that can be adopted towards solving the problems facing Nigeria's agriculture sector are proposed.

Wireless Information and Power Transfer in MIMO Virtual Full-Duplex Relaying System

Abstract: Interrelay interference (IRI) is known to degrade the performance of virtual full-duplex (FD) relaying schemes. Although interference avoidance and cancelation strategies have been proposed in the existing literature, most studies reflect the traditional information theoretical viewpoint of interference as a degrading factor on information decoding (ID). However, from energy harvesting (EH) perspective, the IRI could be beneficial. This motivates the study of simultaneous wireless information and power transfer in decode-and-forward multiple input multiple output virtual FD relaying system, where the IRI serves as an additional source of energy to the relay. To manage the degrading effect of the IRI on the ID receiver, transmit antenna selection is proposed at the relay. In addition, precoding matrices that optimize the ID and EH receivers are jointly designed. The simulated results show that although IRI could be a degrading factor from the information viewpoint, it can be properly managed and exploited for EH at the relay while maintaining the end-to-end data rate. In addition, the results show that the end-to-end information rate and harvested energy can be simultaneously achieved using the proposed precoders.

SINR Maximization Beam Selection for mmWave Beamspace MIMO Systems

Abstract: Beamspace multiple-input multiple-output (MIMO) systems employ beam selection algorithms based on the sparsity of the beamspace channel to reduce the number of radio-frequency chains required in multi-user systems. In this article, we address the problem of selecting multiple beams to each user. Specifically, we propose a beam selection scheme subject to signal to interference plus noise ratio (SINR) maximization. The proposed beamspace beam selection algorithm is developed in two stages. In the first stage, each user is assigned a non-overlapping beam determined by Kuhn-Munkres assignment algorithm. In the second stage, the selected beams in the previous stage are augmented with additional beams from an $M$ -dominant beam set subject to a sum-rate maximization criterion. The performance of the proposed scheme is verified by simulations, and the results show a near-optimal performance in terms of the achievable sum-rate. Also, a significant improvement in terms of energy efficiency is achieved compared to the conventional beam selection scheme.

Location-Aware Coordinated Beam Alignment in mmWave Communication

Abstract: Beam alignment is required in mmWave communication to ensure high data transmission with reduced interference. However, system performance can be degraded due to high beam alignment overhead. In this paper, we propose an efficient beam alignment algorithm in mmWaveband communications by exploiting the location information of the mobile user and possible reflectors. The proposed scheme allows the mobile user and the base station to jointly search a small number of beams within the error boundary of the noisy location information, the selected beams are then used to guide the search of future beams. Simulation results show that the proposed algorithm does not only improve the performance of the system in the presence of noisy location information but also reduce the beam alignment overhead, power and time resource even with narrow beams. In addition, the results on the achievable rate offer some useful insight on the performances of the proposed algorithm based on the simulations settings.

An Overview of Internet of Things (IoT) and Data Analytics in Agriculture: Benefits and Challenges

Abstract: The surge in global population is compelling a shift toward smart agriculture practices. This coupled with the diminishing natural resources, limited availability of arable land, increase in unpredictable weather conditions makes food security a major concern for most countries. As a result, the use of Internet of Things (IoT) and data analytics (DA) are employed to enhance the operational efficiency and productivity in the agriculture sector. There is a paradigm shift from use of wireless sensor network (WSN) as a major driver of smart agriculture to the use of IoT and DA. The IoT integrates several existing technologies, such as WSN, radio frequency identification, cloud computing, middleware systems, and end-user applications. In this paper, several benefits and challenges of IoT have been identified. We present the IoT ecosystem and how the combination of IoT and DA is enabling smart agriculture. Furthermore, we provide future trends and opportunities which are categorized into technological innovations, application scenarios, business, and marketability.

Digital Twin: Enabling Technologies, Challenges and Open Research

Abstract: Digital Twin technology is an emerging concept that has become the centre of attention for industry and, in more recent years, academia. The advancements in industry 4.0 concepts have facilitated its growth, particularly in the manufacturing industry. The Digital Twin is defined extensively but is best described as the effortless integration of data between a physical and virtual machine in either direction. The challenges, applications, and enabling technologies for Artificial Intelligence, Internet of Things (IoT) and Digital Twins are presented. A review of publications relating to Digital Twins is performed, producing a categorical review of recent papers. The review has categorised them by research areas: manufacturing, healthcare and smart cities, discussing a range of papers that reflect these areas and the current state of research. The paper provides an assessment of the enabling technologies, challenges and open research for Digital Twins.

Internet-of-Things (IoT)-Based Smart Agriculture: Toward Making the Fields Talk

Abstract: Despite the perception people may have regarding the agricultural process, the reality is that today's agriculture industry is data-centered, precise, and smarter than ever. The rapid emergence of the Internet-of-Things (IoT) based technologies redesigned almost every industry including “smart agriculture” which moved the industry from statistical to quantitative approaches. Such revolutionary changes are shaking the existing agriculture methods and creating new opportunities along a range of challenges. This article highlights the potential of wireless sensors and IoT in agriculture, as well as the challenges expected to be faced when integrating this technology with the traditional farming practices. IoT devices and communication techniques associated with wireless sensors encountered in agriculture applications are analyzed in detail. What sensors are available for specific agriculture application, like soil preparation, crop status, irrigation, insect and pest detection are listed. How this technology helping the growers throughout the crop stages, from sowing until harvesting, packing and transportation is explained. Furthermore, the use of unmanned aerial vehicles for crop surveillance and other favorable applications such as optimizing crop yield is considered in this article. State-of-the-art IoT-based architectures and platforms used in agriculture are also highlighted wherever suitable. Finally, based on this thorough review, we identify current and future trends of IoT in agriculture and highlight potential research challenges.

A Survey on the Role of IoT in Agriculture for the Implementation of Smart Farming

Abstract: Internet of things (IoT) is a promising technology which provides efficient and reliable solutions towards the modernization of several domains. IoT based solutions are being developed to automatically maintain and monitor agricultural farms with minimal human involvement. The article presents many aspects of technologies involved in the domain of IoT in agriculture. It explains the major components of IoT based smart farming. A rigorous discussion on network technologies used in IoT based agriculture has been presented, that involves network architecture and layers, network topologies used, and protocols. Furthermore, the connection of IoT based agriculture systems with relevant technologies including cloud computing, big data storage and analytics has also been presented. In addition, security issues in IoT agriculture have been highlighted. A list of smart phone based and sensor based applications developed for different aspects of farm management has also been presented. Lastly, the regulations and policies made by several countries to standardize IoT based agriculture have been presented along with few available success stories. In the end, some open research issues and challenges in IoT agriculture field have been presented.

Internet of Things (IoT) and Agricultural Unmanned Aerial Vehicles (UAVs) in smart farming: A comprehensive review

Abstract: Internet of Things (IoT) and Unmanned Aerial Vehicles (UAVs) are two hot technologies utilized in cultivation fields, which transform traditional farming practices into a new era of precision agriculture. In this paper, we perform a survey of the last research on IoT and UAV technology applied in agriculture. We describe the main principles of IoT technology, including intelligent sensors, IoT sensor types, networks and protocols used in agriculture, as well as IoT applications and solutions in smart farming. Moreover, we present the role of UAV technology in smart agriculture, by analyzing the applications of UAVs in various scenarios, including irrigation, fertilization, use of pesticides, weed management, plant growth monitoring, crop disease management, and field-level phenotyping. Furthermore, the utilization of UAV systems in complex agricultural environments is also analyzed. Our conclusion is that IoT and UAV are two of the most important technologies that transform traditional cultivation practices into a new perspective of intelligence in precision agriculture.