Abstract

     One of the main challenges in the design of wireless ad-hoc and sensor networks is to reduce energy consumption and radio interference and collision, which are strictly and strongly correlated to the transmission range of the nodes. In this article, the transmission ranges of sensors in sparse Wireless Sensor Networks (WSN) is theoretically analyzed and is shown that the transmission ranges of sensors can be significantly reduced in this type of WSNs without losing any connection. Next, a method is presented to calculate reduced transmission ranges. In this method, an iterative transmission range adjustment mechanism is used to select an almost transmission range while no information is needed on the location of nodes or the distance between nodes. This method is very efficient and its communication overhead is low. It can be used as a pre-step of any routing algorithm in order to decrease energy consumption and radio interference in targeted scenarios. The simulation results show the efficiency of the proposed method. We got at least 50% improvement in energy consumption in comparison with full power network, in sparse WSNs.

Introduction

     Wireless Sensor Networks (WSNs) have become increasingly popular in recent years, as they offer a powerful and cost-effective solution for monitoring and collecting data from a variety of environments. A Wireless Sensor Network (WSN) consists of a large number of distributed sensor nodes that cooperatively monitor the physical world [1]. Each node in these networks is typically equipped with a wireless communication device, a small microcontroller, a memory unit and a power source. The nodes in a WSN are typically battery-powered and have limited processing power, memory, and communication bandwidth. Therefore, the design of a WSN requires careful consideration of these constraints, such as the choice of communication protocol, data routing algorithms, and energy management strategies [2].

     The complexity of the WSN domain as well as the presence of many sensor nodes unavoidably introduces a large amount of data in these networks that must be processed, transmitted and received. The sheer amount of data generated by WSNs can pose a significant challenge for the network design and operation. The sensors in a WSN can generate data continuously or periodically, depending on the application requirements. This data must be processed, stored, and transmitted to the base station in a timely and efficient manner. So the complexity of the WSN domain and the presence of many sensor nodes can introduce a large amount of data that must be processed, transmitted, and received [3]. Despite their profound advantages, the utilization of WSNs is often battery-powered and strictly limited due to energy constraints. In fact, most of the energy expenditure of a sensor node occurs during wireless communication, and the remaining energy is consumed during sensing and data processing. The radio transceiver of a node consumes a significant amount of energy during data transmission and reception. Therefore, the energy consumption of a node must be carefully managed to ensure the longevity of the network [4]. Transmission power adjustment for a special transmitter-receiver pair depends on several environmental conditions. The transmission power required to reach the receiver is affected by two main factors including distance and wireless connection quality. Distance affects transmission power. As the distance between the transmitter and receiver increases, the signal strength decreases, resulting in a weaker connection.

Conclusions and future works

     We studied the transmission range of sensors in wireless sensor networks in this study, and proposed a simple yet effective distributed transmission power control algorithm for sparse wireless sensor networks. We showed that this algorithm has advantages in many cases. The main idea of algorithm is simple, but performance of algorithm in targeted scenarios is excellent. We analyzed the performance of this method theoretically and show that using this method is worthwhile in some scenarios, especially in sparse wireless sensor networks with high amount of communication traffic. In these scenarios, our method can be used as a pre-step of any routing algorithm and decrease energy consumption and radio interference. As a future work, we intend to design methods to overcome the collisions problem. Designing methods for resisting the algorithm against the sensor failures is another future work. Furthermore we intend to work on using learning methods like Reinforcement learning for power control. Designing a good energy efficient reward mechanism is one of the main challenges of these methods.

Abstract

The Internet of Things (IoT) is becoming pervasive and with each new installation of IoT platforms new and legacy brokers have to be exploited. New internal brokers are those under the control of the platform, while legacy external brokers are those in place managed by third parties. The solution proposed addressed problems of (a) interoperability to reduce set up time to cope with unknown data structures (devices, entities) distributed via brokers; (b) performance by dimensioning both front-end and back-end processes to reach high rates in a broker-based platform, while preserving full capability features of the data warehouse. Interoperability aspects have been addressed by introducing our concepts and a reasoner into an IoT Directory tool to manage Internal and External brokers, automate device discovery and registration from both standard and customized data models. Despite the managed complexity, a broker-based solution turned out to provide high performance. To this end, a specific assessment and architecture tuning have been performed and reported in the paper to give evidence and validation. The proposed integrated IoT Directory has been developed in the context of the Herit-Data Project, and it is currently used in the whole Snap4City network of 18 tenants and billions of data. Snap4City is an open-source IoT platform for Smart Cities and Industry 4.0, which is an official FIWARE platform and solution, EOSC service and libs of Node-RED.

Introduction

The Internet of Things (IoT) defined a paradigm for the computation and communication amongst things, which is becoming every day more and more pervasive and adopted in many different domains [1,2]. It is partially due to the worldwide intense deployment campaign about Low-Power Wide Area Network technologies [3], as well as to many approaches and protocols for communications amongst devices (e.g., Message Queue Telemetry Transport or MQTT, Next Generation Service Interfaces or NGSI, Advanced Message Queuing Protocol or AMQP, Constrained Application Protocol or COAP). The approach is also covering the cloud and fog infrastructures [4,5]. Thus, IoT network infrastructures are becoming every day more complex to be managed due to the networks’ structure and existence of several protocols, formats, and concepts [1,6]. Hence, the complexity is growing in terms of data management, not only for huge amount of data but also for interoperability and abstraction levels needed to data managing. Relevant aspects to be considered are security and privacy [7] on specific data models and entities. To increase the complexity, there is a range of different owners and managers who may control different parts of such IoT networks [8].

In this context, the concept of Gateway is relevant for any segments of IoT networks connecting, as well as for the Web of Things, WoT [9]. Gateways may be integrated with one or more Brokers to send/receive data to/from Devices/entities. The Gateways and Brokers are typically compliant with a single protocol and may be managed by third parties with respect to data management platform. In some cases, they are provided as public services for several interested customers in the same area (for example: Proximus for LoraWAN services [10]). A Gateway may abstract from the IoT Broker level managing multiple brokers for multiple organizations/tenants (which can be regarded as customers of Gateway services to manage several Devices), via some API and/or Web user interface. Typical IoT Brokers can only manage one organization, and thus are single tenant, meaning they broker messages using topic/entity concepts (which can be regarded as the key for subscription on that specific device/entity) without any internal partition of services, but as a sort of family of devices and subscriptions. Some IoT Brokers can be multi-tenant, such as the FIWARE Orion Broker [11,12], which provides support for partitioning the served devices/entities/topics in groups, and each of them may have a dedicated service/path for a specific scope (or a specific customer). Furthermore, devices of different tenants could exist physically in different places (even having identical identifiers, IDs), and the subscription to the broker’s tenant may imply receiving all messages/services in the partition in push. That is feasible only if the subscriber knows the service/path identifier and, in the event of access control, the subscriber has the grant to access the broker’s services. Different IoT Devices connected to the same broker adopt the same protocol, may use different data structures/models and have the same semantic information.

Conclusions

The proliferation of IoT devices, brokers, networks, data models, operators and tenants, makes the harmonization and management of IoT Platform a hard goal. This paper offers an analysis and a comparison amongst relevant existing platforms, and it points out the basic requirements to achieve such aims. These identified requirements are in most cases not addressed by main platforms which prefer to stay on their own end-to-end solutions with limited interoperability and capacity of exploiting legacy IoT networks in place, in terms of performance. The proposed solution addressed problems of (a) interoperability by reducing set up time to efficiently detect and learn how to process unknown data structures (devices, entities) distributed via brokers; (b) performance by dimensioning the front-end and back-end processes to reach high rates in a broker-based platform, while preserving full capabilities features of data warehouse.

As to interoperability, the main identified and solved problems are those related to a large variety of Data Models coming from non-controllable External Brokers. The issue has been solved by designing and implementing a harvester and reasoner that is capable to automatically recognize/understand and map the new data models/types into those already known by Knowledge Base. This approach, together with the definition of a comprehensive meta model and dictionary, has allowed to speed up the process more than 800 times. The harvesting and comprehension process can be periodically performed to keep the platform updated with any newly defined data models by third party brokers. Furthermore, the process is helped by Km4City ontology and Data Dictionary to recognize the new data types and models according to the semantic domain.

Abstract

In WSN sensor nodes are connected to their neighbor nodes by a wireless channel and these all nodes are operated on a battery to perform any operations. So improving the lifetime of WSN is a major research challenge by effective utilization of each and every node’s energy. The lifetime of WSNs can be improved in three steps: path creation, path selection, and power saving. In existing works, path selection has the major role to utilize and enhance lifetime. In the proposed PStack algorithm, path generation is a major concern, and routing is applied. It takes advantage of and solves the limitations of existing algorithms using the stack concept in WSN. The proposed algorithm shows a better result than the improved LEACH protocol because it uses the data structure with graph theory.

Introduction 

Basic foundation of any kind of network communication is path generation from source to destination. Especially in the WSN path generation has a major role. A better path generating between source and destination leads to optimized load balancing and achieves high lifetime. Most of the existing models have single backbone meaning that it creates a single path in network with single backbone, may not be ideal to prolong the lifetime[1]. A simple WSN model is considered with six sensor nodes and a sink as depicted in figure1. It is understood that all sensor nodes are kept active 24X7 irrespective of whether is it in use or not. This leads to unnecessary usage of battery power leading to drain down quickly. Therefore the node automatically disconnected itself from its neighbours[5].

In this work node’s energy means all node’s energy not only the selected nodes energy. Because improving the node’s energy may not able to prolong the lifetime, it can be happen only when all nodes energy will be utilize effectively without wasting any nodes energy. According to the review of literature, there are various techniques introduced and implemented to improve the lifetime of WSN. All these techniques were applied either in routing algorithms or region (area) of WSN as cluster. These techniques may be categories as: 1. WSN with single sink and 2.WSN with more than one sink.

CONCLUSION

PStack algorithm in WSN eliminate the drawbacks of all existing protocol, which is used for the improvement of lifetime of WSN such as AODV, CDS, KMAT, DSR, NBS, VBS and cluster. PStack algorithm results will be in form of the number of stacks with different sizes. Number of stacks represents the number of paths from source to sink and size of stack represents the number of sensor nodes in particular path which having the significant roles for path selection technique. This is the great way to improve the lifetime of any kinds of WSN. This algorithm works more effectively when density of nodes are high. It also supports for static as well as dynamic nodes in WSN.

Limitation of this work is that this assumption may have chances to become wrong if sensor nodes participated in any communication without knowledge of sink, or sink didn’t able to update the energy level of nodes properly

Abstract

A computer network system in a company or agency generally uses more than one Internet Service Provider (ISP) to maintain the quality of its internet services. When one of the ISP’s services that are used is interrupted and the internet connection is lost, then the techniques that can be used are load balancing and failover. This study aims to establish a network of two ISPs using load balancing methods and failover techniques with MikroTik. Load balancing to equalize traffic loads and stabilize internet connections for each client and apply failover techniques with 2 ISPs. The method used is the Network Development Life Cycle which redesignates the new network topology by analyzing Quality of Service (QoS) based on the THIPON standard. Based on the test results, the QoS value obtained is 3.75 during busy internet usage hours and the QoS value is 4 at normal hours. Overall, the implementation of computer networks using load balancing techniques with the PCC method showed good changes, this was concluded based on the results of distributing questionnaires before and after implementation from the previous score of 0.4 rising to 0.89.

Introduction

1. Introduction Indonesia currently has many internet users with an increase from year to year. World Bank data in 2020 shows that as many as 53.7% of the total population of Indonesia are recorded as active internet users, which is equivalent to 127.5 million people[1]. The rapid development of this can affect the traffic load because the server is used with excessive amounts (overload). In the meantime, companies, educational institutions, and cafes sometimes use more than one network to meet their needs[2]. The goal is that internet connection disconnection can be avoided when one of the ISP services used is experiencing problems. To overcome this, the load balancing technique is deemed appropriate to be applied. The load balancing technique can work well when requests coming from clients have managed to balance the balance evenly, so that traffic can run optimally, maximize output, and minimize response time to avoid overloading one of the connection lines[3].

One of the companies is experiencing network instability problems and the network’s inability to support its daily operational performance. By using two types of ISP and making MikroTik as a load balancer using failover technique, it is hoped that it will be able to overcome these obstacles. Technically, load balance is not doubling the connection, but dividing the workload or connection load. MikroTik is also expected to be able to optimize bandwidth for each client who wants to access the internet. The mechanism is that MikroTik will mark packets that want to access the internet, then choose which ISP path to go through and equalize the load on the two ISPs. Meanwhile, if one gateway connection is being disconnected, the failover technique will make the other gateway automatically support all network traffic. This is supported by the results of previous studies using two types of ISPs that successfully spread the number of connection loads on all ISP gateways used in a balanced manner[4].

Conclusions

The design and implementation of a computer network with a load balancing technique using the PCC method based on MikroTik router, which is applied when ISP 1 fails in connection, ISP 2 will immediately take over the existing traffic data so that the internet connection can run well. Meanwhile, the performance of a computer network that uses load balancing techniques with the PCC method that has been applied, through the data from the Quality of Service (QOS) analysis consisting of delay, jitter, packet loss and throughput with a QoS value of 3.75 during busy internet usage hours. (08.00-12.00 WITA) and QoS value 4 at normal hours (13.00-16.00 WITA). The results of research on the implementation of computer networks that use load balancing techniques with the PCC method also show good changes. This is based on the results of distributing questionnaires before and before implementation from the previous one getting a score of 0.4, increased to 0.89.

Further development is recommended to use an ISP with a fixed bandwidth (Dedicated) service and not a shared bandwidth or up to internet service, because when this research was implemented, there was no infrastructure in the Sumba Jaya area, so the author still uses shared bandwidth internet services. Furthermore, the use of installed access points is one of the causes in determining the QOS of an internet network, this is proven when the PT XYZ office is still installed with an outdoor access point that is more than 5 (five) years old, the network becomes unstable.

Abstract

     Data storage for attendance at a company or agency is usually stored in a local or cloud database. This type of storage has several issues, such as privacy and data integrity, because several parties will fully regulate privacy and data integrity. Therefore, a data storage system is needed that can provide privacy, security, and data integrity to maintain the authenticity of sensitive data. This study wants to develop to implement blockchain technology to store employee attendance data from the HR department in a company. Employee attendance data is taken from the Angular web application integrated with a permissioned blockchain framework called Hyperledger Composer. This study chose Hyperledger Composer because this type of blockchain has a fast validation time. Hyperledger Composer has a Representational State Transfer Application Programming Interface (REST API) named composer-rest-server, which allows Hyperledger blockchain to interact with other components. The implementation results show that Hyperledger Composer can be functionally used as data storage for the attendance management and Payroll system. In addition, Hyperledger Composer performance is measured by evaluating block transaction times. The evaluation of the Hyperledger Composer is done in three ways: directly within the Hyperledger Composer, using the Angular web application through the REST API, and using JMeter through the REST API. As a result, testing for making transaction blocks varies from 1 – 17ms on an experiment directly in Hyperledger Composer, 5 – 296ms through the REST API using JMeter tools, and 1 – 4270ms through the Angular Web Application. The result shows that the performance of the REST API produced by the composer-rest-server is recorded faster than Ethereum. With these results, composer-rest-server can handle systems that require fast transaction times, such as voting systems, health monitoring, and the Internet of Things (IoT) application, because the average time to conduct transactions is still under one second. Thus, Hyperledger as attendance data storage can provide privacy and data integrity.

Introduction

     Blockchain is a distributed digital ledger technology that Nowadays, the development and use of technology are developing more rapidly in various fields, one of which is information technology. Information technology is a technology used to get, store, organize, process, and manipulate the amount of data to produce relevant and accurate information. The attendance management and payroll system are some of the information systems on financial activities required in a company or agency. The use of this information system can provide an accurate report of attendance records and payroll. The attendance management and payroll system is a system that processes the attendance information to determine the total salary of each employee. Attendance data is sensitive information that must be maintained for authenticity because it can affect the number of salaries to be paid.

Conclusion

     The blockchain attendance management and payroll system design can be well implemented. All functions of the Hyperledger Composer component and the Angular web application are running properly and according to the design. Hyperledger Composer can communicate with the other components through the REST API provided by the composer-rest-server. The REST API provided by composerrest-server performs well through JMeter with an average transaction time of 198ms and the total time required for 100 transactions of 1.98 seconds compared to Ethereum Blockchain. Blockchain technology can support the attendance and payroll system, so this system has advantages in data security and data integrity.

Abstract

1. Introduction

2. Related Work

3. VoRtex—Metaverse System Description

4. Evaluation of Metaverse Platforms

5. Conclusions

References

Abstract

     Metaverse platforms are becoming an increasingly popular form of collaboration within virtual worlds. Such platforms provide users with the ability to build virtual worlds that can simulate real-life experiences through different social activities. In the paper, we introduce a novel platform that provides assistive tools for building an educational experience in virtual worlds and overcoming the boundaries caused by pandemic situations. Therefore, the authors developed a high-level software architecture and design for a metaverse platform named VoRtex. VoRtex is primarily designed to support collaborative learning activities with the virtual environment. It is designed to support educational standards and it represents an open-source accessible solution developed using modern technology stack and metaverse concepts. For this study, we conducted a comparative analysis of the implemented VoRtex prototype and some popular virtual world platforms using Mannien’s matrix. Afterwards, based on the comparison, we evaluated the potential of the chosen virtual world platform and the VoRtex platform for online education. After an interactive demonstration of the VoRtex platform, participants were asked to fill out a questionnaire form. The aim was to enable participants to identify the main advantages of online teaching using the VoRtex platform. Finally, the authors analyzed benefits and disadvantages of collaborative learning between the metaverse platform and real-world classroom sessions.

Introduction

     Over the years, people have used various technologies to adapt education to modern mediums. Online learning using personal computers (PC) and mobile devices has become very popular in the last few years. Modern learning platforms include sharing, monitoring, personalized experience, and different client applications (desktop, mobile, web-based) for accessing the content. Moreover, new mediums that we can use for online learning such as metaverse or virtual worlds (VWs) platforms are emerging. We can define VWs as follows: “Simulated persistent space based on the interaction with a computer, inhabited by several users, who are represented by iconic images called avatars, who can communicate with each other in a synchronized way” [1]. VW integrates several technologies into one platform, which includes audio, video, webcam, text chat, voice chat using voice over Internet protocol (VoIP), graphical editors, and digital avatars. For building VWs, we can use software development tools such as game engines. Game engines provide basic building blocks (rendering, object manipulation, scripting, and other computer graphics features) for VW development. In addition, for designing a high-quality computer graphics-based software, we should follow the best practices and standards regarding user experience design and software optimization [2]. Collaborative virtual environments (CVEs) are VWs that provide a richer collaborative arena for social encounters and community building. Another name for CVEs is virtual learning environments (VLEs), the universal term in the literature associated with education. Examples of CVEs include social entertainment, multiplayer games, interactive art, simulations, distance learning, architectural walk-throughs, cultural heritage, etc.

Conclusions

     In this paper, we have compared and evaluated the potential of a VW platform for educational purposes. Furthermore, we evaluated the user experience on the VoRtex platform. Firstly, we reviewed the related work regarding collaboration and learning in VWs. Secondly, we described the concept and purpose of VW platforms. Thirdly, we introduced the VoRtex software architecture for collaboration and e-learning inside VWs. Afterwards, we compared VW platforms Vircadia, Sansar, and the VoRtex prototype using Mannien’s matrix. Based on the comparison, features offered by the emerging VW platforms enabled simulation of real-life interaction and experience through the support of desktop PCs or VR devices. Afterwards, we provided a survey in which we evaluated the user experience in the VoRtex prototype for Windows PC. Based on the results of survey, we found that the users respond positively to the VoRtex platform, and the usage of VWs in online learning could overcome boundaries during the COVID-19 pandemic.

     In the end of the comparison process, Vircadia provided an overall slightly better educational experience, based on the listed criteria, in comparison to the VoRtex and Sansar with a sufficiently suitable solution (74 scores) for educational purposes. VoRtex has less content than the other two platforms. However, the VoRtex platform regarding the results from Mannien’s matrix comparative analysis has a security advantage, the most important aspect in the educational sector [29]. In addition, VoRtex’s innovative design provides out-of-the-box assistive tools for teachers such as presentation and video panels that are not common features in the other two platforms. Planned improvements after the next technology milestone using Unreal Engine 5 and MetaHuman will bring the platform graphically to a hyper-photorealistic level and initially provide more assets to content creators [32]. In our future work, we will measure and evaluate the VW software architecture and improve the prototype to simplify the VW platform design process for educational purposes. Furthermore, one of the top priorities for moving forward is to have users carry out routine assessments of VoRtex to help the development of the platform and make it more feature-rich. VoRtex source code and project updates are available on GitHub [36].

Research Goal, Methodology, and Contributions

The research goal is to understand, identify, and analyze potential threats and vulnerabilities in the Internet of Medical Things (IoMT) devices, and provide an analysis of solutions to the issues identified from a cybersecurity perspective. Through the investigation of the Mobile Cardiac Telemetry 3 Lead and the remote patient monitoring kit from Vivify Health, a critical analysis of security issues and potential solutions is presented to reach the research goal.

IoMT is a growing application of IoT technology. It directly improves the quality of life of patients and eases the burden on healthcare providers. IoMT consists of IoT devices specifically developed to meet the needs of patients and healthcare facilities. IoMT is developed for remote patient monitoring, intensive care, and context awareness, which gathers information about a patient’s environment. IoMT can also be utilized beyond direct patient treatment, such as medical equipment and medication management.

I have conducted investigative analysis of two IoMT devices, the Mobile Cardiac Telemetry 3 Lead (MCT3L) and the remote patient monitoring kit from Vivify Health. I have formulated a series of questions to meet the research goal. These questions serve as the basis for the analysis of the IoMT environment. I met with a local hospital that provided the MCT3L User Guide, which contained the specifications for the MCT3L. I also met with Wellstar Home Health for a demonstration of the remote patient monitoring kit from Vivify Health. The information gathered from these sources provided me with the information to conduct analyses to fulfill the research goal.

My contributions to the field include the analysis of real IoMT devices, their threats and vulnerabilities, and solutions to further protect them. Furthermore, the work in this thesis illustrates the lacking security countermeasures found in IoMT devices currently deployed. This work contributes to the IoMT literature by conducting a thorough investigation of specific devices, the MCT3L, and the remote patient monitoring kit. The IoMT security literature is lacking in thorough technical examination of devices that are currently deployed. This work provides details of IoMT devices and the security risks they impose, along with a comprehensive analysis of possible solutions. These solutions consist of using secure communication protocols, using multi-factor authentication for user equipment, understanding the device manufacturer’s role in security, implementing robust security policies and procedures organization wide, utilizing network hardening techniques and network segmentation, providing IoMT security training and education, using lightweight security protocols, and using blockchain and cloud computing technologies.

Abstract

     The Internet of Things (IoT) is a concept that has attracted significant attention since the emergence of wireless technology. The knowledge diffusion of IoT takes place when an individual disseminates his knowledge of IoT to the persons to whom he is directly connected, and knowledge creation arises when the persons receive new knowledge of IoT, which is combined with their existing knowledge. In the current literature, several efforts have been devoted to summarising previous studies on IoT. However, the rapid development of IoT research necessitates examining the knowledge diffusion routes in the IoT domain by applying the main path analysis (MPA). It is crucial to update prior IoT studies and revisit the knowledge evolution and future research directions in this domain. Therefore, this paper adopts the keyword co-occurrence network and MPA to identify the research hotspots and study the historical development of the IoT domain based on 27,425 papers collected from the Web of Science from 1970 to 2020. The results show that IoT research is focused on IoT applications for smart cities, wireless networks, blockchain technology, computing technologies, and AI technologies. The findings from the MPA address the need to explore the knowledge evolution in the IoT domain. They also provide a valuable guide to disseminate the knowledge of IoT among researchers and practitioners, assisting them to understand the history, present and future trends of IoT development and implementation.

Introduction

     The concept of the Internet of Things (IoT) has been gaining momentum since the emergence of wireless technology [1,2,3,4,5,6]. The fundamental premise of IoT is to connect multiple devices through tools like Radio Frequency Identification (RFID), sensors, actuators, smartphones, by which these devices can communicate with each other [7]. As a dynamic global network infrastructure, IoT relies on smart devices with several capabilities, including sensing, networking, processing, and actuation, thereby facilitating the ability of people and objects to collaborate in heterogeneous and complex environments [8,9,10]. According to the seminal survey of [11], concepts and technologies surrounding IoT can be categorised into three main parts. The first part concerns the internet-oriented vision, which corresponds to the development of IP protocol for allowing smart things to communicate over the internet [12]. The second part is related to the things-oriented vision, which considers IoT a network of identifiable things [13]. This vision is achieved by integrating sensors and pervasive technologies to track objects. The third part concerns the semantic-oriented vision, which focuses on how vast networks of heterogeneous devices and the data they are generating can be controlled, monitored, and managed from a technical perspective [14]. As such, raw data generated from sensor-based systems will be processed and churned out to obtain a better understanding and representations. These visions can be realised through the interconnection and interoperability of sensing and actuating technologies, providing the ability to exchange information across different platforms through a unified framework and enable innovative applications [15].

Conclusions

     This paper conducts a retrospective analysis of five decades of research on IoT, where the main objective was to shed light on IoT and determine the pattern of knowledge diffusion, the key roots over the previous decade, and highlight the current research areas and potential opportunities for further academic investigations. In light of this, we used a multi-step approach to the bibliometric examination of IoT research, employing two complementary analytical methods, the keyword co-occurrence network and MPA, and utilizing the software tools VOSviewer and Pajek in the analysis of publications extracted from the Web of Science (WoS). These two methods aim to systematically investigate the entire domain of IoT based on 27,425 papers retrieved from WoS from 1970 to 2020. The idea of blending both methods provides in-depth insights for researchers to enhance their understanding of IoT development over the past fifty years. To our knowledge, this is the first study that uses four different main paths to investigate the knowledge diffusion trajectories in the IoT domain. The results show that there are five main clusters and the most significant clusters are around IoT applications for smart cities, and thus it is labelled as IoT for smart cities, followed by wireless networks, blockchain technology, computing technologies, and AI technologies. This numerical method helps researchers identify important activities in the IoT domain and unearth the routes of knowledge diffusion on IoT systematically. Accordingly, several insights and recommendations are suggested for the scholars and practitioners to understand the history, present and future trends of IoT development in a new review approach, which is more comprehensive than traditional review methods and bibliometric analysis.

Abstract

CONTEXT

     Automated monitoring of the soil-plant-atmospheric continuum at a high spatiotemporal resolution is a key to transform the labor-intensive, experience-based decision making to an automatic, data-driven approach in agricultural production. Growers could make better management decisions by leveraging the real-time field data while researchers could utilize these data to answer key scientific questions. Traditionally, data collection in agricultural fields, which largely relies on human labor, can only generate limited numbers of data points with low resolution and accuracy. During the last two decades, crop monitoring has drastically evolved with the advancement of modern sensing technologies. Most importantly, the introduction of IoT (Internet of Things) into crop, soil, and microclimate sensing has transformed crop monitoring into a quantitative and data-driven work from a qualitative and experience-based task.

OBJECTIVE

     Ag-IoT systems enable a data pipeline for modern agriculture that includes data collection, transmission, storage, visualization, analysis, and decision-making. This review serves as a technical guide for Ag-IoT system design and development for crop, soil, and microclimate monitoring.

METHODS

     It highlighted Ag-IoT platforms presented in 115 academic publications between 2011 and 2021 worldwide. These publications were analyzed based on the types of sensors and actuators used, main control boards, types of farming, crops observed, communication technologies and protocols, power supplies, and energy storage used in Ag-IoT platforms.

RESULTS AND CONCLUSION

     The result showed that 33 variables measured by various sensors were demonstrated in these studies while 10 actuations were successfully integrated with Ag-IoT platforms. Perennial crops, which introduced less disturbance to Ag-IoT platforms than annual crops, were selected by 64% of researchers. Furthermore, studies in Ag-IoT system development were more focused on outdoor than indoor environments. Ag-IoT systems based on Arduino were most common among the studies while commercial platforms were least adopted, likely due to their inflexibility in customized developments. More researchers focused on agricultural applications than the IoT technology itself. Soil water content-based irrigation scheduling and controlled environment monitoring and controlling were the main applications. Other application areas included soil nutrient estimation, crop monitoring based on multiple vegetation indices, pest identification, and chemigation.

SIGNIFICANCE

     Several potential future research directions were identified at the end of the review, including integration of satellite-based internet connectivity to improve the IoT networks in non-connected farms, development of mobile IoT platforms (drones and autonomous ground vehicles) with continuous connectivity, and the use of edge-computing and machine-learning/deep-learning to enhance the capability of the Ag-IoT systems.

Introduction

     Crops are essential for human life because they provide food, animal feed, fuel, and raw materials for clothing and shelter. Crop yield has to be doubled in 2050 compared to 2009 in order to meet the demand of a growing population while increasing the food quality and reducing production inputs (Fukase and Martin, 2020). Potential solutions to enhance global food security include closing crop yield gaps, reducing food waste, changing dietary habits, and reducing inefficiencies in resource use (Foley et al., 2011). Reducing inefficiencies in input resources (such as water and nitrogen) can be achieved by continuously monitoring crops, soil, and microclimate, and then properly controlling inputs without sacrificing the yield and quality of the crop. Internet of Things (IoT) becomes a key technology that enables continuous monitoring and control in this scenario. The ability to generate (near) real-time quantitative data with high spatiotemporal resolution is a major advantage of IoT systems (Liao et al., 2017). IoTs are considered big data systems due to volumes, velocities, and varieties of data they generate. These data are mined and modeled to elucidate the relationships between inputs and outputs (Tsai et al., 2014). Correlation, trend analysis, classification, and numerical prediction are implemented on the data to reach meaningful control decisions. Compared with the conventional wireless sensor networks, the holistic approach of IoT technology allows users to incorporate data analytics on the big data collected by IoT sensor devices. Generally, connected actuators are enabled to control the inputs to achieve desired application rates. For example, an internet-connected soil water content (SWC) sensor network measures the plant water deficit and uploads data to a cloud-based data analysis platform. The analysis will find the trend of soil water deficit to determine the best time and quantity to apply irrigation water.

Conclusions and future directions

Conclusions

     Ag-IoT is a promising technology that would increase resource use efficiency in agricultural systems, and is an essential tool for digital agriculture transformation. In this paper, we have overviewed impactful research related to Ag-IoT in the past decade. The data collected from these papers were categorized and analyzed under six main Ag-IoT system design parameters namely sensors, sensing platforms and main control board, communication technology and IoT protocols, cloud platforms, power and energy management, and actuators. According to the analyzed data, it is revealed that there is an increased global attention towards the Ag-IoT system-related research in the recent years. However, there are certain research gaps found in the literature. One of them is that the implementations of the sensors and the actuators seem to be limited to soil and environmental parameter monitoring and irrigation controlling. Furthermore, crop macro and micronutrient demand analyses are still at the infant stage due to the non-availability of sensors that can measure nutrients in real-time. Therefore, it is essential to improve the sensor and actuator applications in crop monitoring and controlling. In addition, heterogeneity of the system parameters (such as data, platforms, required power) is a major challenge to the Ag-IoT systems implementation, to which the improvement of the context-awareness could be a solution. Power harness options for Ag-IoT nodes need more exploration as there are limited options available and it would be a big advantage for the perennial crop monitoring. The perception and the network layers of Ag-IoT systems require more improvements to meet the sensor implementation ergonomics and long-range high-throughput data transmission, respectively. Edge computing can be a replacement of the high throughput long-range communication, but to the best of our knowledge, only a limited number of practical applications have been developed based on edge computing to date. Mobile Ag-IoT platforms such as unmanned aerial and ground vehicles have a huge potential to increase the spatiotemporal resolution in Ag-IoT-based monitoring and controlling.