Gateway Node Research Articles

Research on Remote eSIM Provisioning Management Technology for 5G Terminal

The use of eSIM in mobile terminals such as the Internet of Vehicles has become the general trend, and more and more enterprises have put forward clear requirements for the remote provisioning of eSIM. This paper aims to combine 5G technology to analyze remote eSIM provisioning management technology for terminal, and combine algorithm improvement to improve remote eSIM information management and control effects. Moreover, this paper describes in detail the three-layer communication structure in the communication model, the design of edge gateway nodes, and the query mechanism for cloud center request names and data resources. In addition, this paper uses experiments to evaluate the connectivity of the eSIM three-layer communication model and the characteristics of the NDN network. Through experimental research, it can be seen that the remote eSIM provisioning management model proposed in this paper has certain advantages when applied to the Internet of Vehicles compared with the existing remote provisioning management technologies for the Internet of Vehicles. This article takes the Internet of Vehicles as an example to conduct research. At the same time, its support for mobility can be well applied to the Internet of Vehicles to meet the mobility of terminal vehicles. Therefore, it can provide some reference in the subsequent development of Internet of Vehicles technology.

Smart forest monitoring: A novel Internet of Things framework with shortest path routing for sustainable environmental management

AbstractForests play a pivotal role in protecting the environment, preserving vital natural resources, and ultimately sustaining human life. However, the escalating occurrences of forest fires, whether of human origin or due to climate change, poses a significant threat to this ecosystem. In recent decades, the emergence of the IoT has been characterised by the utilisation of smart sensors for real‐time data collection. IoT facilitates proactive decision‐making for forest monitoring, control, and protection through advanced data analysis techniques, including AI algorithms. This research study presents a comprehensive approach to deploying a dynamic and adaptable network topology in forest environments, aimed at optimising data transmission and enhancing system reliability. Three distinct topologies are proposed in this research study: direct transmission from nodes to gateways, cluster formation with multi‐step data transmission, and clustering with data relayed by cluster heads. A key innovation is the use of high‐powered telecommunication modules in cluster heads, enabling long‐range data transmission while considering energy efficiency through solar power. To enhance system reliability, this study incorporates a reserve routing mechanism to mitigate the impact of node or cluster head failures. Additionally, the placement of gateway nodes is optimised using meta‐heuristic algorithms, including particle swarm optimisation (PSO), harmony search algorithm (HSA), and ant colony optimisation for continuous domains (ACOR), with ACOR emerging as the most effective. The primary objective of this article is to reduce power consumption, alleviate network traffic, and decrease nodes' interdependence, while also considering reliability coefficients and error tolerance as additional considerations. As shown in the results, the proposed methods effectively reduce network traffic, optimise routing, and ensure robust performance across various environmental conditions, highlighting the importance of these tailored topologies in enhancing energy efficiency, data accuracy, and network reliability in forest monitoring applications.

Landslide Monitoring and Warning System Based on Wireless Sensor Network

Landslides are common in Indonesia, often caused by factors like heavy rainfall and high soil moisture levels. The Batubrak mini hydro power plant intake area in Lampung province of Indonesia has experienced landslides, prompting the need for an early warning system. This study presents the development of a cost-effective and efficient real-time landslide monitoring and warning system. The system incorporates sensors to measure accelerometer and vibration parameters, enabling real-time data display through a wireless sensor network and SCADA software. Early warnings are issued when triggers are activated. Three sensor nodes were deployed in the intake area for testing, demonstrating their ability to detect, collect, process, and transmit accelerometer and vibration data to the gateway node.

A TECHNIQUE TO SECURE DATA TRANSMISSION IN WIRELESS BODY AREA NETWORKS

The wireless body area networks have contributed to the changes in healthcare sector by enabling continuous monitoring of biomedical parameters remotely on the patient body and offering real time data transmission. Upon collection of the vital signs, they are transmitted to the gateway node which then forwards them to the remote hospital medical servers. Here, these physiological data items are analyzed and necessary action is taken. Such physiological data include electrocardiograms (ECGs), blood pressure, body temperature, blood oxygen levels, respiratory rate, Electroencephalogram (EEG), Electromyogram (EMG), glucose levels, physical activity and Electrodermal Activity (EDA). In this paper, we develop a technique for securely transmitting this sensitive data from the body sensor unit (BSU) to the remote hospital medical server (HMS). KEYWORDS: Sensors, BSU, WBAN, security, privacy

Wormhole attack detection and mitigation model for Internet of Things and WSN using machine learning.

The Internet of Things (IoT) is revolutionizing diverse sectors like business, healthcare, and the military, but its widespread adoption has also led to significant security challenges. IoT networks, in particular, face increasing vulnerabilities due to the rapid proliferation of connected devices within smart infrastructures. Wireless sensor networks (WSNs) comprise software, gateways, and small sensors that wirelessly transmit and receive data. WSNs consist of two types of nodes: generic nodes with sensing capabilities and gateway nodes that manage data routing. These sensor nodes operate under constraints of limited battery power, storage capacity, and processing capabilities, exposing them to various threats, including wormhole attacks. This study focuses on detecting wormhole attacks by analyzing the connectivity details of network nodes. Machine learning (ML) techniques are proposed as effective solutions to address these modern challenges in wormhole attack detection within sensor networks. The base station employs two ML models, a support vector machine (SVM) and a deep neural network (DNN), to classify traffic data and identify malicious nodes in the network. The effectiveness of these algorithms is validated using traffic generated by the NS3.37 simulator and tested against real-world scenarios. Evaluation metrics such as average recall, false positive rates, latency, end-to-end delay, response time, throughput, energy consumption, and CPU utilization are used to assess the performance of the proposed models. Results indicate that the proposed model outperforms existing methods in terms of efficacy and efficiency.

DISASTER MITIGATION FOR PEOPLE WITH CEREBRAL PALSY BASED ON BEHAVIORAL ARCHITECTURE IN RESIDENTIAL USING WIRELESS SENSOR NETWORK

At this time, most houses for persons with disabilities are not yet equipped with a disaster mitigation system. It may be difficult for persons with disabilities to be able to save themselves when a disaster occurs. Therefore, in this study, a system for disaster mitigation, especially fires in the residence of a child with cerebral palsy, has been successfully designed. The optimal placement of the wireless sensor network is decided based on a behavioral architectural analysis using the DepthMapX-0.7.0 software. Behavioral architecture assessment begins by observing patterns of daily activities and a simulation of human movement in the house to find out the most frequent activity places used by children with cerebral palsy. Based on the test results with DepthMapX-0.7.0, it can be concluded that the optimal location of the sensor node points is in the child's bedroom, kitchen, and TV room. The designed wireless sensor network consists of three sensor nodes and a gateway node. Data sampling is performed every 15 seconds. If a fire is identified, the buzzer will emit a warning signal. In addition, the child's family can monitor home conditions from the ThingSpeak.com website and Telegram.

Understanding the security failures of four user authentication schemes for wireless sensor networks in IoT environment

User authentication protocols are applied to provide a secure conversation between participating entities in wireless sensor networks (WSNs). To identify how to ensure security in these schemes, it is imperative to look into the security vulnerabilities of these authentication mechanisms. As a part of this study, we examine the security of four 2-factor authentication schemes for WSNs (namely, Zhang and Wen, Jangirala et al., Maurya and Sastry and Singh et al.). Security verification result shows that they are all confronted by serious security weaknesses (like sensor node capture attack, exposer of session key by gateway node attack, smart card lost attack, malicious gateway node attack, and session-specific ephemeral information loss attack) and lack of important security functionalities (like multi-factor security, perfect forward secrecy, user anonymity and untraceability, and session key security). This research concentrates on the ‘root cause of the problem. This will help in the research and development of reliable and efficient user authentication mechanisms for WSNs. Our research results point out some new challenges in building reliable multi-factor mechanisms of user authentication for WSNs. We additionally identify some significant insights from the cryptanalysis results of these mechanisms.

A provably secure authenticated key agreement protocol for industrial sensor network system

SummaryThe convergence of reliable and self‐organizing characteristics of Wireless Sensor Networks (WSNs) and the IoT has increased the utilization of WSN in different scenarios such as healthcare, industrial units, battlefield monitoring and so forth, yet has also led to significant security risks in their deployment. So, several researchers are developing efficient authentication frameworks with various security and privacy characteristics for WSNs. Subsequently, we review and examine a recently proposed robust key management protocol for an industrial sensor network system. However, their work is incompetent to proffer expedient security and is susceptible to several security attacks. We demonstrate their vulnerabilities against man‐in‐the‐middle attacks, privileged insider attacks, secret key leakage attacks, user, gateway, and sensor node impersonation attacks, and offline password‐guessing attacks. We further highlight the design flaw of no session key agreement in Itoo et al. Therefore to alleviate the existing security issues, we devise an improved key agreement and mutual authentication framework. Our protocol outperforms Itoo et al.'s drawbacks, as demonstrated by the comprehensive security proof performed using the real‐or‐random (ROR) model and the formal verification accomplished using the Automated Validation of Internet Security Protocols (AVISPA) tool.

Energy efficient routing protocol for enhancing the network lifetime in wireless sensor network

Wireless sensor networks (WSNs) confront significant challenges related to battery capacity, as sensor nodes operate on limited energy resources. To address this issue, low energy adaptive clustering hierarchy (LEACH) protocol is commonly employed for power management in WSNs. LEACH is commonly used for power management. Here, sensing region is divided into clusters and sectors, placing a gateway node at the center to minimize energy consumption during data transmission. It employs one-hop, two-hop, or three-hop pathways based on node proximity to the base station (BS) to optimize energy usage. Network performance is assessed using rounds, throughput, and energy usage. MATLAB simulations compare the proposed approach with dual layer LEACH (DL-LEACH) and LEACH, showing significant improvements in network lifetime. The proposed scheme outperforms LEACH by 515% and 347% for 20% and 50% node depletion, respectively. Compared to DL-LEACH, it extends network lifetime by 27% and 59% under similar scenarios. Sectoring, clustering, and multi-hop communication reduce energy consumption, enhancing network lifetime and addressing WSN challenges effectively.

A COMPREHENSIVE ANALYSIS OF ENERGY EFFICIENT WIRELESS SENSOR NETWORK (WSN) PROTOCOLS

Wireless Sensor Networks (WSNs) include many tiny and low energy and cheaper nodes in different areas for measuring the environmental parameters like temperature and humidity. Hence, the usage of WSNs has become an adaptable means of data transfer across different fields due to the advancement of wireless technology. It is noted that these networks,which use nodes for event detection and identification, gather information by means of simple calculations and send it to a particular Base Station (BS) via gateway nodes. The applications of WSNs can be classified into monitoring and tracking,which are used in areas such as environmental monitoring, health diagnostics, military surveillance, and many others.nergy consumption is still a major issue of concern, sensor nodes in particular, use energy in sensing data and transmitting it. Energy savings techniques like clustering and routing protocols are important for increasing the life time of the network.hus, this research aims at analysing the different aspects of improving energy efficiency and network performance,especially in the context of the clustering algorithms, such as the Multi-level Stable and Energy Efficient Clustering (MSEEC) protocol. The paper discusses major issues and suggests some new combined routing approaches for WSNs with the problems connected with fault tolerance, topology, scalability, and power consumption.

Wireless Body Sensor Networks for Real-Time Healthcare Monitoring: A Cost-Effective and Energy-Efficient Approach

Background: The continuous and accurate monitoring of physiological signals is critical for timely medical interventions, particularly in the context of chronic disease management and elderly care. The advent of Wireless Body Sensor Networks (WBSN) and Patient Health Monitoring Systems (PHMS) promises to revolutionize healthcare by integrating real-time data collection with advanced processing and communication technologies, enabling proactive medical responses through the Internet of Things (IoT). Methods: In this study, a WBSN-PHMS framework is proposed, leveraging a network of biomedical sensors to continuously monitor vital signs such as temperature and heart rate. The system includes a gateway node that wirelessly transmits sensor data to a cloud-based storage and processing system. Physiological data are processed in real-time using advanced algorithms to detect anomalies and trigger alerts. The health status is modeled using a function g(v,w(v),∅−1(v(w))−∂i(v,∂))g(v, w(v), \varnothing^{-1}(v(w)) - \partial_i(v, \partial))g(v,w(v),∅−1(v(w))−∂i?(v,∂)), which integrates patient-specific factors and real-time physiological states. The processed data are communicated efficiently through IoT platforms, ensuring that healthcare professionals receive timely alerts via mobile applications and specialized dashboards. Results: The WBSN-PHMS demonstrated high accuracy in detecting abnormal temperature and heart rate patterns, achieving detection rates of 98.61% and 99.43%, respectively. Additionally, the system improved overall patient health monitoring by 98.42%, offering a significant advancement in patient safety and healthcare efficiency. The cost-effectiveness of the system was established with a 96.21% improvement, while energy consumption was reduced by 23%, underscoring the sustainability of the technology. Conclusion: The WBSN-PHMS proves to be a reliable and efficient healthcare monitoring system that enhances patient outcomes through real-time data analysis and rapid medical responses. The system's ability to continuously monitor and analyze physiological signals in a non-intrusive manner positions it as a vital tool in modern medical practice, with the potential to revolutionize remote patient care and monitoring.

QoS-based energy-efficient hybrid routing protocols in RSU assisted VANET using clustering mechanism

ABSTRACT Vehicular ad hoc networks (VANET) communication framework are employed to improve communication between vehicles on the highway and urban roads. Evaluating the best routing path by satisfying the QoS (Quality of Service) plays a substantial role in networking. Researchers for maximising the routing efficiency have employed numerous methods. But these criteria cannot be attained effectively due to certain limitations, including frequent route failure, high overhead, increased packet loss rate, less throughput and packet delivery rate. Hence, this work presents an effective strategy to offer better communication services with less energy consumption and high flexibility using QoS-based energy efficient routing framework with clustering (QoS_EErcF) network model. Initially, different clusters are formed by considering the constraints like node direction, link reliability, speed and distance. The cluster heads (CH) are chosen from the clusters with the dissemination of gateway nodes and cluster members using an Amended rapid cosine similarity-founded clustering mechanism (Arc_SimC). The best routing strategy for transmitting the data from source to destination is performed by using Integrated Pelican with grasshopper optimisation algorithm (IPel_Ghop). Constraints such as bandwidth, node distance, energy, packet loss rate, network traffic and end-to-end delay are considered to find the optimal path. The results are simulated using MATLAB, whereas the energy efficiency of a proposed model is obtained to be 98.37%, and the packet delivery ratio is attained as 99.60%.

Environmental Monitoring System using Wireless Multi-Node Sensors based Communication System on Volcano Observations Drones

Indonesia is on the Ring of Fire and has the world's most active volcanoes. Volcanic activity has a significant effect on the landscape and on the people who live there. The difficulty of evacuating and helping victims requires hard work and sometimes even the safety of the rescue team itself. For this reason, high-tech tools are needed. Unmanned aerial vehicles (UAVs), also called drones, have become a hopeful tool for remote environmental monitoring in recent years. The system design has a monitoring platform, gateway, and sensor nodes attached to the UAV, which monitors the content of toxic gas contamination in the air. Using IoT technology, sensor data is sent wirelessly to a central monitoring station for a thorough and accurate volcanic activity study. This system is a flexible and complete way to monitor volcanic activity, learn more about it, and make it easier to respond to disasters. Tests are also done to measure system speed, including latency, and determine network service quality. The results show that data is successfully sent in real-time from the sensor nodes to the monitoring system. The average Round-Trip time for the payload transmission is 446.046226 ms. This shows how well the system works to send data from the sensors connected to the UAV to the monitoring station. The UAV has sensor nodes and a monitoring system platform. These can be used to build and optimize disaster mitigation systems.

Enhanced centroid-based energy-efficient clustering routing protocol for serverless based wireless sensor networks

Serverless computing is a new concept as cloud computing, which dynamically manages the networks and is applied in Serverless Wireless Sensor Networks (SWSN) to help the networks. These networks are becoming famous for monitoring various physical and environmental factors. Serverless computing also facilitates the networks by offering an extensive range of applications. Different applications have been designed for monitoring purposes where the sensor nodes sense the data and transmit it to the base station through single or multi-hop routing. However, existing routing protocols cannot manage the sensor nodes’ energy issues because of the complex routing processes and depleted their power before their time. Because of these limitations, the nodes close to BS continuously rely on the network for data forwarding. As a result, these nodes cause energy consumption and lead to a useless state. This paper proposes a serverless architecture and designs an Enhanced Centroid-based Energy Efficient Clustering (ECEEC) protocol for SWSN networks. The proposed serverless architecture provides automated scalability, cost-effective services, and stateless execution. In addition, the proposed protocol offers the cluster head selection and its rotation to maximize the energy efficiency in the network. Furthermore, gateway nodes are chosen in every cluster to overcome the load on the cluster head. Simulation results indicated the excellent performance of the proposed protocol as compared to the existing routing protocols concerning network lifetime and energy consumption. The proposed protocol shows better reliability with nodes failing at 650 rounds compared to 600 rounds, especially with 5 % and 10 % Cluster Heads. The proposed protocol exhibits superior energy efficiency consumption of SNs under varying CH percentages, indicating the protocol’s consistent performance across different scenarios.

Energy Efficient for Data Aggregation in Wireless Sensor Networks

Abstract: The Wireless Sensor Networks (WSNs), known for their decentralized and self-configuring properties, utilize sensor nodes to collect and transmit data to a base station. However, due to their sprawling nature and the substantial distances involved, energy management remains a critical challenge in WSNs. To mitigate this, hierarchical clustering has been identified as an effective strategy. This approach involves dividing the network into clusters of a predetermined size, each led by a cluster head selected based on their energy levels and proximity to the base station. The chosen head is typically the node with the least distance to the base station and the highest energy reserve. These heads facilitate inter-cluster communication and data transfer to the base station. This research presents the implementation and enhancement of the WEMER protocol, aimed at prolonging the lifespan of WSNs. The WEMER protocol initially segments the network into clusters with respective heads and designates leader nodes to relay data from the cluster heads to the base station. Enhancements to this protocol include the deployment of gateway nodes close to the base station. These nodes receive data from the leader nodes, which in turn acquire data from the cluster heads, thus boosting network longevity. Implemented and tested in MATLAB, the enhanced WEMER protocol demonstrates significant improvements over its predecessor. The results indicate a reduction in the number of inactive (dead) nodes, an increase in active (alive) nodes, a higher data packet transmission rate, and improved overall energy efficiency.

Multipath Load Balancing in MANET via Hybrid Intelligent Algorithm

The Mobile Adhoc Network (MANET) is a vital network that is vulnerable to energy and security restrictions. Because of node mobility, building a routing protocol to offers an effective and acceptable means of routing data with minimum packet loss, less energy consumption, and extending network lifetime has become a difficult challenge in MANETs. Most of the current MANET routing protocols lack the strategy of precise load-balancing. A recent survey on load distribution in MANET shows shortest-path MANET routing protocols using centrally located nodes in many routes. Since few nodes have to carry excessive loads, congestion increases, leading to undesirable effects such as long delays, lower packet delivery, and higher routing overhead, which shows the need for proper balancing models. In this work, multipath load balancing with the proposed NUSOA is used in MANETs to reduce energy usage and packet loss. Here, the data packets are distributed through gateway nodes, which are selected by the various features such as path cost, link cost, residual energy, and distance. Proposed hybrid optimisation termed as Namib Updated Shepherd Optimisation Algorithm (NUSOA) which is the mixture of both Namib Beetle Optimisation (NBO) and Shuffled Shepherd Optimisation Algorithm (SSOA) to choose optimal gateway nodes. Moreover, the optimal path is chosen based on load balancing with the constraints of congestion detection and node availability of the path using the proposed hybrid optimisation.

Civil Aeronautical Ad Hoc Network Zero-Overhead Clustering Algorithm Based on Realtime Position Information of the Aircraft

Clustering is an important means to solve the poor scalability of aeronautical ad hoc networks (AANET). To improve the stability and performance of AANET and avoid unnecessary waste of resources caused by civil aircraft in communication, we proposed a zero-overhead clustering algorithm according to the real-time position of the aircraft based on the known trajectory. Firstly, the route and trajectory models are used to obtain geographical coordinates by the aircraft positioning algorithm. On this basis, the geographical cluster and cluster head region are divided in order to complete the cluster setting. Considering the aircraft maintenance cluster generation time updates, we use the communication sub-cluster generation algorithm to control the size of the cluster, and also, the flexibility of cluster hops is guaranteed by the subsidiary cluster members. The continuity of communication and the scalability of the cluster are maintained by the gateway node, thereby forming a network structure and increasing the stability of clusters. Finally, the actual route data are used to simulate the performance of the algorithm. The experimental and analytical results show that clustering and maintenance of the algorithm have zero overhead. Additionally, compared with the traditional algorithm, our proposed method can maintain a reasonable number of clusters, reduce the frequency of cluster head replacement, reduce the number of cluster members entering and leaving the cluster and avoid the loss of control of cluster heads to cluster members. So, it has important application value in the field of civil aviation.

Energy efficient gateway based routing with maximized node coverage in a UAV assisted wireless sensor network.

Ad-hoc wireless sensor networks face challenges of optimized node deployment for maximizing coverage and efficiently routing data to control centers in post disaster events. These challenges impact the outcome for extending the lifetime of wireless sensor networks. This study presents a uav assisted reactive zone based EHGR (energy efficient hierarchical gateway routing protocol) that is deployed in a situation where the natural calamity has caused communication and infrastructure damage to a major portion of the sensor network. EHGR is a hybrid multi layer routing protocol for large heterogeneous sensor nodes (smart nodes, basic nodes, user handheld devices etc.) EHGR is tailored to meet two important concerns for a disaster hit wsn ie. optimized deployment and energy efficient routing. The first part of EGHR focuses on maximized coverage during node deployments. Maximized coverage is an important aspect to be considered during the event of disaster since most of the nodes loose coverage and are detached from the wireless sensor network. The first part of EHGR uses state of the art game theory approach to build a model that maximizes the coverage of nodes during the deployment phase from all participating entities i.e. nodes and uavs. Rather than fixing the cluster head as is the case in traditional cluster-based approaches EHGR uses the energy centroid nodes. Energy centroid nodes evolve on the basis of aggregated energy of the zone. This approach is superior to simply electing cluster head nodes on the basis of some probability function. The nodes that fail to achieve any successful outcome from the game theory matching model fail to get any association. These nodes will use multi hop d2d relay approach to reach the energy centroid nodes. Gateway relay nodes used with the game theory approach during the deployment of the uav assisted wsn improves the overall coverage by 25% against traditional leach based hierarchical approaches. Once the optimum deployment phase is completed the routing phase is initiated. Aggregated data is sent by the energy centroid nodes from the ECN nodes to the servicing micro controller enabled un manned aerial vehicles. The routing process places partial burden of zone formation and data transmission to the control center for each phase on the servicing uavs. Energy centroid nodes engage only in the data aggregation process and transmission of data to servicing uav. Servicing-uavs reduce energy dissipated of the entire zone which result in gradual decrease of energy for the zone thus increasing the network lifetime. Node deployment phase and the routing phase of EHGR utilize the computations provide by the mirco controller enabled unmanned aerial vehicles such that the computationally intensive calculations are offloaded to the servicing uav. Experiment results indicate an increase in the first dead node report, half dead node report, and last dead node report. Network lifetime is extended to approximately 1800 rounds which is an increase by ratio of 100% against the traditional leach approach and increase by 50% percent against the latest approaches as highlighted in the literature.

Future Hybrid Technology for Pay TV Platform

The main objective of this study is to analyze the potentiality of new technology of TV broadcasting and video distribution systems and how to adapt to the new trend of video viewing experience and design a future generation TV for the Bangladesh Pay TV industry. This research is based on Bangladesh and the interest of Bangladesh's Pay-TV industry delves into a novel approach aimed at mitigating these challenges by harnessing terrestrial or mobile networks for video broadcasting, thereby upgrading the old-fashioned broadcasting system or diminishing reliance on conventional internet-based streaming for mobile. This study adapts to the latest practice and implementation of ATSC 3.0 Terrestrial broadcasting and video streaming technology enhancement and business success along with emerging 5G network feasibility. ATSC 3.0 terrestrial broadcasting for mobile users has a significant impact on view experience, and seamless video transmission without the usage of internet data, especially in rural areas of the country where the 4G network is very limited. Local Gateway Node will receive ATSC 3.0 live TV and locally added offline video or streaming apps injected through API to deliver household through private CDN. This study offers a comprehensive technical feasibility, benefits, and implications of this innovative approach, upgradation of terrestrial broadcasting system highlighting its potential to revolutionize video delivery to mobile users. This study analyzes the technology evolution and adaptability with the recent trend of video content viewing experience, the importance of this study is significant for Bangladesh's pay-TV market to secure the future business.

Design of Crop Irrigation Decision-Making System Based on ZigBee Technology

Abstract: To promote the high-quality development of agriculture, meet the needs of agricultural products grown in greenhouses, and achieve precise monitoring of greenhouse plants, a small greenhouse micro-environment multi-parameter monitoring system was designed and implemented. The system consists of three parts: a monitoring node, a gateway node, and a remote management platform. The monitoring node used the ESP32 microcontroller as the main control chip, combined ZigBee technology, and embedded different sensors to complete the collection and transmission of environmental parameters. In the gateway node, the 4G Data Transfer Unit module was used as the carrier, and the communication protocol was used to realize data communication between the monitoring terminal and the gateway. The remote management platform was based on the PyCharm development platform. It used the PyQt5 graphical user interface (GUI) toolkit to complete the design of the host computer monitoring platform, establish a database, and realize the storage and analysis of environmental parameters. The remote management platform embedded the crop reference evapotranspiration, online calculation model, to provide irrigation decisions for greenhouse crop management and improve the applicability and accuracy of irrigation decisions. After the experimental test platform was built to test the system communication distance, communication reliability, control reliability, and data reliability, the small greenhouse micro-environment multi-parameter monitoring system designed in this paper can operate stably for a long time. Its functions meet the expected requirements and are in line with modern requirements for multi-parameter monitoring of smart greenhouses.