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The Internet of Things (IoT) vision requires increasingly more sensor nodes interconnected and a network solution that may accommodate these requirements accordingly. In wireless sensor networks, there are energy-limited devices; therefore techniques to save energy have become a significant research trend. Other issues such as latency, range covera...
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... Key parameters for ZigBee and LoRaWAN technology[50][51][52] ...
The Internet of Things (IoT) has orchestrated various domains in numerous applications, contributing significantly to the growth of the smart world, even in regions with low literacy rates, boosting socio-economic development. This study provides valuable insights into optimizing wireless communication, paving the way for a more connected and productive future in the mining industry. The IoT revolution is advancing across industries, but harsh geometric environments, including open-pit mines, pose unique challenges for reliable communication. The advent of IoT in the mining industry has significantly improved communication for critical operations through the use of Radio Frequency (RF) protocols such as Bluetooth, Wi-Fi, GSM/GPRS, Narrow Band (NB)-IoT, SigFox, ZigBee, and Long Range Wireless Area Network (LoRaWAN). This study addresses the optimization of network implementations by comparing two leading free-spreading IoT-based RF protocols such as ZigBee and LoRaWAN. Intensive field tests are conducted in various opencast mines to investigate coverage potential and signal attenuation. ZigBee is tested in the Tadicherla open-cast coal mine in India. Similarly, LoRaWAN field tests are conducted at one of the associated cement companies (ACC) in the limestone mine in Bargarh, India, covering both Indoor-to-Outdoor (I2O) and Outdoor-to-Outdoor (O2O) environments. A robust framework of path-loss models, referred to as Free space, Egli, Okumura-Hata, Cost231-Hata and Ericsson models, combined with key performance metrics, is employed to evaluate the patterns of signal attenuation. Extensive field testing and careful data analysis revealed that the Egli model is the most consistent path-loss model for the ZigBee protocol in an I2O environment, with a coefficient of determination (R²) of 0.907, balanced error metrics such as Normalized Root Mean Square Error (NRMSE) of 0.030, Mean Square Error (MSE) of 4.950, Mean Absolute Percentage Error (MAPE) of 0.249 and Scatter Index (SI) of 2.723. In the O2O scenario, the Ericsson model showed superior performance, with the highest R² value of 0.959, supported by strong correlation metrics: NRMSE of 0.026, MSE of 8.685, MAPE of 0.685, Mean Absolute Deviation (MAD) of 20.839 and SI of 2.194. For the LoRaWAN protocol, the Cost-231 model achieved the highest R² value of 0.921 in the I2O scenario, complemented by the lowest metrics: NRMSE of 0.018, MSE of 1.324, MAPE of 0.217, MAD of 9.218 and SI of 1.238. In the O2O environment, the Okumura-Hata model achieved the highest R² value of 0.978, indicating a strong fit with metrics NRMSE of 0.047, MSE of 27.807, MAPE of 27.494, MAD of 37.287 and SI of 3.927. This advancement in reliable communication networks promises to transform the opencast landscape into networked signal attenuation. These results support decision-making for mining needs and ensure reliable communications even in the face of formidable obstacles.
... manages the transmission of downlink packets and sends control signals to the end devices, which the gateways convert and transmit over the LoRaWAN radio channel. Further communication is established with application servers, which may be operated by third-party organizations, enabling a single network server to support multiple application layers [44]. The LoRaWAN architecture is depicted in Figure 1 below. ...
Indoor localization of wireless nodes is a relevant task for wireless sensor networks with mobile nodes using mobile robots. Despite the fact that outdoor localization is successfully performed by Global Positioning System (GPS) technology, indoor environments face several challenges due to multipath signal propagation, reflections from walls and objects, along with noise and interference. This results in the need for the development of new localization techniques. In this paper, Long-Range Wide-Area Network (LoRaWAN) technology is employed to address localization problems. A novel approach is proposed, based on the preliminary division of the room into sectors using a Received Signal Strength Indicator (RSSI) fingerprinting technique combined with machine learning (ML). Among various ML methods, the Gated Recurrent Unit (GRU) model reached the most accurate results, achieving localization accuracies of 94.54%, 91.02%, and 85.12% across three scenarios with a division into 256 sectors. Analysis of the cumulative error distribution function revealed the average localization error of 0.384 m, while the mean absolute error reached 0.246 m. These results demonstrate that the proposed sectorization method effectively mitigates the effects of noise and nonlinear signal propagation, ensuring precise localization of mobile nodes indoors.
... Focusing on the communication technologies suitable to SA scenarios, where IoT devices are generally deployed in wide outdoor areas, the Long Range Wide Area Network (LoRaWAN) protocol (de Carvalho Silva et al., 2017), defined by the no-profit (LoRa , is well-known and commonly used for its effectiveness in longrange communication and its ability to operate efficiently, even in the presence of obstacles. In fact, the LoRaWAN protocol has a significant potential for IoT agricultural applications (e.g., soil, plants and air monitoring, irrigation, etc.), as discussed by Miles et al. (2020). ...
The exploitation of modern technologies in heterogeneous farming scenarios with different crops cultivation is nowadays an effective solution to implement the concept of Smart Agriculture (SA). Following this approach, in this study the tomato plants’ response to different irrigation regimes is investigated through the implementation of an Internet of Things (IoT)-oriented SA data collection and monitoring system. In particular, the experimentation is conducted on tomatoes grown at three different irrigation regimes: namely, at 100%, 60%, and 30% of the Italian irrigation recommendation service, denoted as Irriframe. The proposed platform, denoted as Agriware, is able to: (i) evaluate information from heterogeneous data sources, (ii) calculate agronomic indicators (e.g., Growing Degree Days, GDD), and (iii) monitor on-field parameters (e.g., water consumption). Different plant-related parameters have been collected to assess the response to water stress (e.g., Soil Plant Analysis Development (SPAD), chlorophyll content, fluorescence, and others), along with leaf color and final production evaluations. The obtained results show that the best irrigation regime, in terms of plant health and productivity, corresponds to 60% of Irriframe, allowing significant water savings for the cultivation.
... In the architecture of LoRaWAN, the end devices in star-to-star topology communicate using LoRa and the data are communicated by using LPWAN architecture. Gateways of LoRa operate as a transparent bridge that converts the RF messages into IP packets and likewise [73]. Researchers have been working on providing a better communication network in Smart Grids based on LoRaWAN as it uses low power and low cost as compared to RF mesh technologies [74]. ...
Smart Grid is a way of providing bidirectional energy flow with the integration of latest communication technologies and advanced control methods to overcome the issues associated with the current power grid such as unidirectional power flow, resource wastage, reliability, security, enhanced quality, and increasing demand of energy. Integrating Internet of Things (IoTs) makes Smart Grid hyperaware and agile to enhance the efficiency, reliability, and sustainability of electricity distribution. IoT-enabled Smart Grids use IoT devices and sensors to collect real-time data, allowing for automated monitoring, predictive maintenance, and better demand management. This study comprehensively reviews various wireless technologies for IoT-enabled Smart Grids that could be integrated into home area networks (HANs), neighborhood area networks (NANs), and wide-area networks (WANs). This work provides a comparison of wireless technologies for HANs, NANs, and WANs in terms of data rates, range, adaptability, internet protocol support, and various other parameters. IoT technologies, including ZigBee, Z-wave, Bluetooth, Wi-Fi, NFC, 6LoWPAN, wireless HART, and Thread, are suggested for operations in HANs according to the customer requirements with their operating characteristics. Similarly, for NANs and WANs, long-term evolution (LTE), WiMax, and LPWAN are explored in terms of requirements of utilities. The study further analyzes the applications of IoT-enabled Smart Grids and elaborates on the associated challenges and issues.
... The conservation of both energy and network resources is facilitated by this measure [59]. • GreenM2M employs energy-efficient communication protocols, including ZigBee [60] and LoRaWAN [61,62], which effectively reduce energy consumption during the data transmission process. • The utilization of GreenM2M facilitates energy-efficient and sustainable machine-to-machine communication, thereby providing discernable advantages in environmental monitoring applications, smart grid systems, and smart transportation networks [63,64]. ...
The Internet of Things (IoT) has experienced exponential expansion, raising questions about its sustainability and environmental impact. In response, the developing discipline of Green Internet of Things(GreenIoT) seeks to address these problems by encouraging energy-saving and environmentally friendly IoT deployment practices. The technological environment of the GreenIoT is thoroughly explored in this article, including enabling technologies , simulators and platforms, smart applications, open projects, information on certificates and compliance , and open research challenges. The article focuses on intelligent applications that use GreenIoT concepts to meet sustainability objectives in a variety of industries, including smart buildings, transportation, agriculture, and healthcare. It demonstrates the revolutionary potential of GreenIoT in creating sustainable and environmentally friendly urban settings by outlining the fundamental characteristics, advantages, and actual implementations of these applications. The paper also highlights the value of open projects and initiatives in the GreenIoT space, looking at teamwork and research projects that promote innovation and advance energy-efficient IoT deployments, particularly in the context of India. The paper also discusses the significance of certificate and compliance information in ensuring that environmental standards and laws are followed in GreenIoT implementations. The study concludes by outlining the open research challenges in the GreenIoT, including creating specific GreenIoT architectures, controlling infrastructure complexity, resolving environmental security issues, and investigating energy-efficient communication protocols. These difficulties offer chances for more research, invention, and development in the area. It serves as a valuable resource for researchers, practitioners, and policymakers curious about the crosswords of IoT and sustainability.
... LoR-aWAN offers a transmission range of up to 5 kms in urban areas and 15 kms in rural areas (Semtech Corporation, 2024), vastly outstripping the range capabilities of other wireless communication protocols such as WiFi, Bluetooth, and ZigBee, all of which are typically limited to under 100 m (Challoo et al., 2012;Fan et al., 2022). LoRaWAN is designed to be highly power-efficient, making it suitable for battery-operated sensor networks, whereas WiFi and Bluetooth tend to consume more power (de Carvalho Silva et al., 2017). In terms of bandwidth, LoRaWAN provides lower bandwidth compared to WiFi and Bluetooth, typically supporting data rates from 0.3 kbps to 27 kbps (Adelantado et al., 2017). ...
Monitoring urban green spaces (UGSs) is crucial for achieving sustainable urban development and ecological resilience. Leveraging LoRaWAN technology, a wireless environmental sensing system was developed and implemented to monitor soil moisture dynamics across seven diverse UGSs over a year. Analyses revealed notable variations in soil moisture influenced by vegetation types, soil conditions and physical settings. Seasonal trends indicated lower summer soil moisture in some UGSs resulting from increased evapotranspiration, while others maintained higher soil moisture due to more frequent irrigation. The soil moisture response to rainfall was quantitatively modeled, demonstrating the increase in soil moisture is highly positively dependent on rainfall amount and negatively dependent on initial moisture level. Both factors were significant (p<0.001) in most cases, and the models’ adjusted R2 values were all above 0.65 except for one node. The findings also unveiled more dynamic ranges of UGS runoff coefficients than government guideline values, especially high runoff coefficients (0.4 to 1.0) for rainfall events above 50 mm. Therefore, although existing UGSs can help absorb smaller storms, proactive drainage systems are needed for UGSs to handle extreme events. The study highlights LoRaWAN's efficacy in urban environmental monitoring and provides valuable insights for managing and optimizing UGSs, especially in stormwater management.
... Therefore, a Long Range Wide Area Network (LoRaWAN) is implemented which provides the ability to communicate over long distances in an energy efficient way. The protocol as well as the network system aritecture are defined by the LoRaWANs architecture which is described as a "star of stars" [22]. In this implementation the IoT PTs are connected to a LoRaWAN-Server via LoRaWAN-Gateways accordingly to the star topology. ...
Digital Twins (DTs) are becoming an empowering and pivotal element in many industries to exploit modern IT technologies across all sectors and gain significant benefits from preexisting as well as greenfield systems. This paper introduces a novel approach to building management and research in laboratory environments, utilizing Building Information Modeling (BIM), DTs, the Internet of Things (IoT), and Extended Reality (XR). The work focuses on generating accurate 3D building models from point cloud scans, improving BIM’s utility in structures lacking pre-existing digital models. Central to this approach is the integration of IoT sensors, tracking indoor air quality and occupancy. This data, combined with DTs of laboratory equipment, facilitates dynamic insights of transdisciplinary work at research and educational projects. Our models uniquely provide live data interaction, seamlessly linking the virtual and physical realms through DTs and XR technologies as an immersive interface. One of the problems at research institutes is the broad range of hazardous measuring devices, some of which require urgent safety precautions. Therefore, based on our models and technologies, we propose an XR-based collaborative platform for transdisciplinary research teams enabling immersive and intuitive interaction. By comprehensively gathering all the data, it is possible to continue investigating how social dynamics affect research environments and projects. This approach aims to make technology more attuned to the social dimensions of laboratory use. The paper highlights the potential of BIM, DTs, IoT, and XR to not only create and update models post-construction but also to enrich them with operational data, offering a socially aware perspective in research management.
... For example, Ayoub et al. [17] explore the various aspects of LPWAN network technologies and their suitability for applications with mobility requirements. Another study by Jonathan et al. [18] compares LoRaWAN with other proprietary LPWAN network technologies. Aldahdouh et al. [19] analyses LPWAN as a 5G candidate, in comparison with other emerging technologies (NB-IoT, Sigfox, and LTE-M). ...
... The modulation and physical layer protocol used result in a long-range communication with low data rate, enabling low energy consumption for battery-operated IoT devices [18]. The LoRa Alliance [42], a non-profit association of companies, standardizes the MAC features of LoRa, promoting the development and adoption of this technology by means of an open standard for LPWAN solutions. ...
In the past decade, with the rapid proliferation of Internet of Things (IoT) devices new applications have emerged in diverse fields such as agriculture, smart cities, and healthcare. In this context, LoRaWAN, a Low-Power Wide Area Network protocol, has gained significant adoption. Its advantages, including low-power consumption and long-range communication capabilities, make it an ideal solution for IoT communication. Simulation tools have played a crucial role in facilitating experimentation and advancing the implementation of the LoRaWAN protocol. However, effectively modelling these experiments present a significant challenge. Through a comprehensive survey of the literature on LoRaWAN, we have identified variations in parameter configuration among different works and observed a lack of sufficient information in most of them, thereby impeding result reproducibility. This paper offers a comprehensive overview of LoRaWAN technology, encompassing its architecture and underlying technologies such as LoRa and LPWAN. Furthermore, we present and compare the main simulation tools currently available for LoRaWAN, discuss the parameters that significantly impact the performance of a LoRaWAN network, and explore how researchers have configured these parameters to model their simulation experiments.
... Apart from the abovementioned challenges, some other facts about IoT communication protocols must also be addressed. Numerous analysis studies of the protocols may consider the following topics: estimation of the collision rate, channel load, single device maximal throughput and maximum transmission unit (MTU), mobility and roaming, and proposing possible solutions for performance enhancement [150]. Clustering approaches, fog computing modes, peer-to-peer communications, gateway densification Complexity and interoperability [140][141][142][143] Lack of defined architectural standard, risk of vendor lock-in, security threads Flexible protocol designing, standardization, fog or edge computing ...
The Internet of Things (IoT) will bring about the next industrial revolution in Industry 4.0. The communication aspect of IoT devices is one of the most critical factors in choosing the device that is suitable for use. Thus far, the IoT physical layer communication challenges have been met with various communications protocols that provide varying strengths and weaknesses. This paper summarizes the network architectures of some of the most popular IoT wireless communications protocols. It also presents a comparative analysis of some of the critical features, including power consumption, coverage, data rate, security, cost, and quality of service (QoS). This comparative study shows that low-power wide area network (LPWAN)-based IoT protocols (LoRa, Sigfox, NB-IoT, LTE-M) are more suitable for future industrial applications because of their energy efficiency, high coverage, and cost efficiency. In addition, the study also presents an Industrial Internet of Things (IIoT) application perspective on the suitability of LPWAN protocols in a particular scenario and addresses some open issues that need to be researched. Thus, this study can assist in deciding the most suitable IoT communication protocol for an industrial and production field.
... Devices that require large amounts of real-time data collection and analysis use 5G transmission technology because of its high transmission rate, high reliability, and low latency. Devices that require only periodic data collection and analysis use LoRaWan transmission technology because of its longrange and low-cost advantages [8]. AI and Machine Learning technologies, which use AI and machine learning algorithms to analyze patient data to provide personalized health assessment, prediction, and recommendations, e.g., a machine learning model can be used to predict the risk of a patient's disease or monitor abnormalities. ...
With the increasing maturity of the Internet of Things (IoT) technology, a new development trend of smart healthcare has been born. This paper, based on the introduction of the current development status, application, and prospects of smart healthcare, mainly focuses on the use of IoT sensors and big data and information systems in smart healthcare and then introduces the relevant technologies involved in wearable devices based on IoT sensors and home environment sensors, as well as the overall operational framework. It also analyzes the case studies of two smart healthcare companies, Sense care and Tencent Cloud, and introduces the smart healthcare technologies they are currently mainly applying. In addition, this report also analyzes the prospects of IoT sensor-based, big data and information systems in the development of smart healthcare, describes some of the current application scenarios and possible areas of application in the future and evaluates the benefits and challenges of their application in the field of smart healthcare.
