The Internet of Things Research in Agriculture: A Bibliometric Analysis

An in-depth analysis of Internet of Things (IoT) applications expertise for agriculture. This article's primary purpose is to provide a comprehensive and organized review of IoT research in agriculture themes. Although recent research has offered some pertinent information regarding the analysis of IoT applications in agriculture, further information is needed. Bibliometric analysis is utilized to objectively investigate, and develop information knowledge of IoT applications in agriculture. The papers investigated and examined the themes of IoT-agriculture by analyzing the co-occurrence keywords. The analysis began by picking 550 papers from the Scopus database that were published from 2003 to May 2023. The results show that IoT agriculture papers have grown rapidly since 2015 until now. The three journals that published the most IoT agricultural publications are Sensors (Switzerland), Computers and Electronics in Agriculture, and IEEE Access. Based on the co-occurrence keywords, the focus of IoT paper in agriculture is wireless sensors network (WSN) and radio frequency identification (RFID) for agricultural monitoring, smart agriculture with IoT blockchain and machine learning, IoT greenhouses with cloud computing and artificial intelligence (AI), components of IoT agriculture, precision agriculture with low power low range (LoRa) communication network and IoT cloud platform, smart farming with sensor networks and automation. The study provided an understanding of themes of the IoT agriculture that has been carried out and its future growth. The future of IoT application will elaborate a system efficient, consumes less energy, and emits less carbon dioxide. It has begun by combining IoT-agriculture with the technology edge-fog-cloud layer

An efficient quality of services based wireless sensor network for anomaly detection using soft computing approaches

Wireless sensor network (WSN) is widely acceptable communication network where human-intervention is less. Another prominent factors are cheap in cost and covers huge area of field for communication. WSN as name suggests sensor nodes are present which communicate to the neighboring node to form a network. These nodes are communicate via radio signals and equipped with battery which is one of most challenge in these networks. The battery consumption is depend on weather where sensors are deployed, routing protocols etc. To reduce the battery at routing level various quality of services (QoS) parameters are available to measure the performance of the network. To overcome this problem, many routing protocol has been proposed. In this paper, we considered two energy efficient protocols i.e. LEACH and Sub-cluster LEACH protocols. For provision of better performance of network Levenberg-Marquardt neural network (LMNN) and Moth-Flame optimisation both are implemented one by one. QoS parameters considered to measure the performance are energy efficiency, end-to-end delay, Throughput and Packet delivery ratio (PDR). After implementation, simulation results show that Sub-cluster LEACH with MFO is outperforms among other algorithms.Along with this, second part of paper considered to anomaly detection based on machine learning algorithms such as SVM, KNN and LR. NSLKDD dataset is considered and than proposed the anomaly detection method.Simulation results shows that proposed method with SVM provide better results among others

IoT protocols, architectures, and applications

The proliferation of embedded systems, wireless technologies, and Internet protocols have made it possible for the Internet-of-things (IoT) to bridge the gap between the physical and the virtual world and thereby enabling monitoring and control of the physical environment by data processing systems. IoT refers to the inter-networking of everyday objects that are equipped with sensing, computing, and communication capabilities. These networks can collaborate to autonomously solve a variety of tasks. Due to the very diverse set of applications and application requirements, there is no single communication technology that is able to provide cost-effective and close to optimal performance in all scenarios. In this chapter, we report on research carried out on a selected number of IoT topics: low-power wide-area networks, in particular, LoRa and narrow-band IoT (NB-IoT); IP version 6 over IEEE 802.15.4 time-slotted channel hopping (6TiSCH); vehicular antenna design, integration, and processing; security aspects for vehicular networks; energy efficiency and harvesting for IoT systems; and software-defined networking/network functions virtualization for (SDN/NFV) IoT

An Assessment of Shortest Prioritized Path-Based Bidirectional Wireless Charging Approach Toward Smart Agriculture

The agriculture sector has witnessed a transformation with the advent of smart sensing devices, leading to improved crop yield and quality. However, the management of data collection from numerous sensors across vast agricultural areas, as well as the associated charging requirements, presents significant challenges. This paper addresses the major research problem by proposing an innovative solution for charging agricultural sensors. The introduction of an energy-constrained device (ECD) enables wireless charging and transmission of soil data to a centralized server. The proposed ECDs will enable enhanced data collection, precision agriculture, optimized resource allocation, timely decision-making, and remote monitoring and control. A bidirectional wireless charging drone is employed to efficiently charge the ECDs. To optimize energy usage, a prioritized Dijkstra algorithm determines the ECDs to be charged and plans the shortest route for the drone. The wireless charging drone landing-charging station achieves an efficiency of 91.3%, delivering 72 W of power within a 5 mm range. Furthermore, the ECD possesses a data transmission range of 100 m and incorporates deep sleep functionality, allowing for a remarkable 30-day battery life.publishedVersio

Modelització i disseny d'un recol·lector d'energia mecànica per l'alimentació d'un node sensor sense fils

La recol·lecció d'energia mecànica vibracional està rebent un interès considerable com a font d'energia per l'alimentació de nodes sensors sense fils. Aquest treball presenta el disseny i modelització d'un recol·lector d'energia mecànica des de la definició de la font de vibracions, fins el disseny i simulació del recol·lector fent servir components piezoelèctrics com a transductors d'energia però també utilitzats com a cantileves que, amb l'ajuda d'una massa l'extrem, s'aconsegueix treballar a la freqüència d'interès. En aquest treball veurem quanta potència mecànica genera el sistema vibracional amb les característiques dissenyades, quanta potència elèctrica s'aconsegueix extreure, i si aquesta és suficient per alimentar un node sensor sense fils.La recolección de energía mecánica vibracional está recibiendo un interés considerable como fuente de energía para la alimentación de nodos sensores inalámbricos. Este trabajo presenta el diseño y modelización de un recolector de energía mecánica desde la definición de la fuente de vibraciones, hasta el diseño y simulación del recolector utilizando componentes piezoeléctricos como transductores de energía, pero también utilizados como cantilevers que, con la ayuda de una masa en el estremo, se consigue trabajar a la frecuencia de interés. En este trabajo veremos cuánta potencia mecánica genera el sistema vibracional con las característica diseñadas, cuánta potencia eléctrica se consigue extraer, y si ésta es suficiente para alimentar un nodo sensor inalámbrico.Vibrational mechanical energy harvesting is receiving considerable interest as a power source for powering wireless sensor nodes. This project presents the design and modeling of a mechanical energy harvester from the definition of the source of vibrations, to the design and simulation of the harvester using piezoelectric components as energy transducers, but also used as cantilevers which, with the help of a mass at the free end, it manage to work at the frequency of interest. In this work we will see how much mechanical power the vibrational system generates with the designed characteristics, how much electrical power it can extract, and if this is enough to power a wireless sensor node