Zigbee based Wireless Sensor Network Architecture for Agriculture Applications

Wireless Sensor Networks (WSNs) consist of small nodes with sensing, computation, and wireless communications capabilities. Many routing protocol have been specifically designed for WSNs. And energy awareness is an essential design issue. In this paper, We study the routing protocol of wireless sensor network and describe the ZigBee based wireless sensor network architecture, analyze the principles of tree-structured routing and AODV routing, and then apply Zigbee technology to intelligent parking system.

Objective: Wormhole attack is a serious threat to Wireless Sensor Networks (WSN) due to its wireless broadcast nature of communication, multi hop nature and resource constraints. Hence, to enhance the security and energy efficiency of a WSN, energy efficient Intrusion Detection System (IDS) is needed to detect and mitigate the attacks. In this paper, an Energy Efficient Intrusion Detection System (EE-IDS) has been proposed for IEEE 802.15.4 based WSN to detect and mitigate the effect of wormhole attacks. Methods/Statistical Analysis: The wormhole attack is detected by using the optimized watchdog system. The optimized watchdog mechanism is a trust based method which is used to evaluate the validity of all the nodes of the network. In proposed approach, the optimization has been done in the selection of watchdog nodes, in order to consume less energy compared to that of the existing approaches. The detection of wormhole attack is also completely relies on the three main factors like trustworthiness, packet delivery ratio and end-to-end delay. Findings: The proposed EE-IDS is examined through extensive simulations by considering static and mobility model, and then it is compared with the existing IDS for detecting wormhole attacks. The performance of zigbee WSN is analyzed in terms of metrics such as packet delivery ratio, average end-to-end delay and energy consumption for static model. In mobility model, the Proposed EE-IDS is evaluated in terms of detection rate, false positive rate and detection time. Application/ Improvements: The proposed EE-IDS is used to detect the wormhole attack and improve the energy efficiency in zigbee based wireless sensor networks, which can be used for military, environmental, health and commercial applications.

The agricultural scenario seems to be one of the most promising application areas for WSN due to the necessity of providing the agricultural production chain in terms of precision and quality. This involves a careful system design, since requirements are very strict, battery life-time maximization, robustness, recovery strategies, network flexibility and re-configurability. This paper implements zigbee based wireless sensor network in agriculture such as monitoring of environmental conditions like weather, soil moisture content, soil temperature, soil fertility, weed detection, water level, monitoring growth of the crop, precision agriculture, automated irrigation facility and storage of agricultural products. The aim of this project is to monitor and maintain the farm from any part of the world through internet. Monitoring is done with the help of wireless sensor networks and all the control process is done with the help of the microcontrollers. Wireless cameras are used to feed live video of the farm to any part of the world. With the help of this project, modern technologies and new ideas can be implemented in the farm sector of our country. A farmer can see the real condition of his farm and also control his farm from any part of the world by logging into farming website. This makes the Indian farmers feel comfortable and reduces the risks involved in irrigation. The idea has the potential to attract entrepreneurs to invest in the agricultural sector.

Telemedicine aided by wireless sensor networks (WSN) has recently become a healthcare trend. Many previous studies have adopted the ZigBee-based WSN to implement a platform and/or a telemedicine system. However, the low data rate and bandwidth have limited the maximum number of nodes in a WSN during continuous and simultaneous transmission. The issue of low data throughput has not been addressed in previous reseazch. In this study, we propose an arrhythmia-aware system, and a new DSPbased WSN platform is developed for the high compression performance of physiological data in a ZigBee-based WSN. Proven by simulations and several real tests, the combination of the proposed platform and the sensor nodes can lead to more bandwidth conservation and extend the WSN scale for the next generation of telemedicine system.

WSN is one of the most efficient technologies in intelligent communication and because of its advantages, this technology has been utilized in various applications. By using WSNs, different types of data can be collected and analyzed in wide environments. The high variety of applications and types of data available in this network can cause several challenges about heterogeneous data routing. This research, presents a Fuzzy Model for Content-Centric Routing (FMCCR) in WSN to solve these challenges. The performance of FMCCR is based on two basic steps: "topology control", and "data transmission through content-centric and fuzzy logic-based routing algorithm". In the first step of FMCCR, the network topology is constructed. In the second step of the proposed method, data transmission paths are determined based on network topology and content type, and data transmission is performed. The performance of FMCCR has been evaluated in a simulation environment and the results have been compared with previous algorithms. The results show that FMCCR reduce energy consumption and improve the traffic load distribution in the network in addition to increasing the network lifetime. According to the results, FMCCR can increase network lifetime at least 10.74% and at the same time, deliver at least 88.1% more packets through the network, compared to previous methods. These results, prove the efficiency of the proposed method for using in real-world scenarios.

This system is used for monitoring the speed, torque, efficiency, voltage & current by employing ZigBee based wireless sensor network. Embedded system is used for acquiring electrical signals from the motors in a non-invasive way. The speed and torque estimation is done locally. An embedded system is used to control the speed of the motor the values calculated by the embedded system are transmitted to the monitoring unit through ZigBee based wireless sensor network and it can be monitored locally in PC. The main advantages of using ZigBee are low maintenance cost, security, reliability and through output. Using simulation, the characteristic graph for speed, torque, output voltage and output current can be obtained.

This paper is intended to design a ZigBee wireless network node based on the advanced RISC machines (ARM), so as to facilitate the network usage process. The performance of the new sensor is subject to antenna test and simulation experiment. The HFSS simulation method is adopted, and the antenna size and scanning frequency are optimized through analyzing the research status of ZigBee technology and the working principle of ZigBee protocol stack based on parameters, such as, the return loss and direction of the antenna, which not only increases the accuracy of analysis and but also reduces the reflection coefficient. The experimental results show that when L2 is 14. 9mm, the effect is the best, and Sll is -26.6 dB. Based on the above findings, it is concluded that the integrated antennas on the printed circuit board (PCB) board can reduce the production cost of the antennas; thus, IFA antennas can meet the requirements of ZigBee based wireless sensor network in term of antenna performance.

In a ZigBee network, low-cost, low-power sensor nodes are deployed to carry out specific tasks like environment sensing, home automation, human and animal condition monitoring, and robot navigation monitoring etc. Normally the network comprises of numerous sensor nodes deployed in different locations and a coordinator node where the sensor nodes report back the sensed data for possible analysis and further action. For certain applications it is desirable to be able to locate the sensor node within the network. Currently localisation can be achieved using time dependent methods (TOA and TDOA) or received signal strength (RSS). Time dependent approaches require time synchronisation at all times which can be difficult to achieve. RSS based method is simple and cost effective but require at least three anchor nodes for a nodes location to be calculated via triangulation. Such a method can increase the complexity and cost of a network deployment. This paper presents a single anchor based location system which utilizes a differential two-element antenna array to perform node localization. An experimental system is introduced and results demonstrate the effectiveness of the proposed system. The anchor node, which can also be the network gateway, is connected to two dipole antennas separated by ⋋/2. The relative phase of each antenna can be varied using a phase shifter. The combined output of the two antennas can be used to create sum and difference radiation patterns, and to steer the antenna radiation pattern. Experimental validation was performed using seven XBee sensor nodes. Accurate azimuthal localization (relative to the anchor node) can be achieved and range estimation can be made with minimal errors. Adaptive path-loss model estimation can further improve range estimation. Overall, this cost effective localisation system performs well for ZigBee based wireless sensor networks.

When designing a wireless sensor network based on ZigBee, it is very important to choose the right network topology, especially in networks with many nodes such as residential areas. Choosing the wrong topology will have an impact on the performance of the wireless sensor network as a whole because it will cause a large delay value. To overcome this, in this study a ZigBee-based wireless sensor network simulation was carried out using an environmental model consisting of several residential units, with one ZigBee device for each house. In addition, three ZigBee network topologies namely mesh, star, and tree are used in this simulation. This is done to determine which topology model will work best in a residential environment. The housing used for the simulation in this study is Citraland Waterfront City Housing which is located in Palu City, Central Sulawesi Province, Indonesia. By using simulations in the Opnet Modeler 14.5 application, it is known that the star topology on the ZigBee network is suitable for application in residential areas with a large number of nodes. This can be seen from the highest throughput values and the lowest media access delay, end-to-end delay, hop number, and packet dropped values compared to tree and mesh topologies.

In mission critical wireless sensor networks (WSNs) accurate timestamping of the occurrence of events measured by the sensor nodes is often required together with a high degree of reliability. While precise timestamping requires synchronization of the sensor nodes, reliability is obtained by adding redundancy in all potential single point of failure nodes. In this paper, we focus on a ZigBee-based WSN using two personal area network (PAN) coordinators with different PAN identifiers (IDs) and, for this configuration, we propose a solution where if the primary PAN coordinator goes down, connections are transferred to the other by changing the PAN ID of the nodes. Our proposed solution provides significant gains in terms of recovery speed and timing synchronization accuracy in comparison to a solution that is proposed in the literature.

Moisture sensor acquires data of moisture content and water height of farmland; the data are transmitted by wireless sensor network and stored in data server to provide data mining and decision support for users, the utilization of wireless moisture sensor network could facilitate the excellent growth of crops and sustainable development of water resources. Based on self-design moisture sensor and actual monitoring needs of farmland moisture, this paper presents the architecture of wireless moisture sensor network and format of moisture data packet, designs the mechanisms of hierarchical storage, hierarchical error control and retransmission. Especially, the paper analyzes and simulates the mechanism of error control from respects of consuming time and correcting error ability, simulation results show that BCH coding is more suitable for wireless moisture sensor network than RS coding.

The integration of solar energy into smart grids requires high-efficiency power conversion to support grid stability. However, Partial Shading Conditions (PSCs) remain a primary obstacle by inducing multiple local maxima on P–V characteristic curves. This paper presents a hardware-aware and memory-enhanced Maximum Power Point Tracking (MPPT) approach based on a modified Dragonfly Algorithm (DA) for grid-connected microinverter-based photovoltaic (PV) systems. The proposed method utilizes a quasi-switched Boost-Switched Capacitor (qSB-SC) topology, where the DA is specifically tailored by combining Lévy-flight exploration with a dynamic damping factor to suppress steady-state oscillations within the qSB-SC ripple constraints. Coupling the MPPT stage to a seven-level Packed-U-Cell (PUC) microinverter ensures that each PV module operates at its independent Global Maximum Power Point (GMPP). A ZigBee-based Wireless Sensor Network (WSN) facilitates rapid data exchange and supports ‘swarm-memory’ initialization, matching current shading patterns with historical data to seed the population near the most probable GMPP region. This integration reduces the overall response time to 0.026 s. Hardware-in-the-loop experiments validated the approach, attaining a tracking accuracy of 99.32%. Compared to current state-of-the-art benchmarks, the proposed model demonstrated a significant improvement in tracking speed, outperforming the most recent 2025 GWO implementation (0.0603 s) by approximately 56% and conventional metaheuristic variants such as GWO-Beta (0.46 s) by over 94%.These results confirmed that the modified DA-based MPPT substantially enhanced the microinverter efficiency under PSC through cross-layer parameter adaptation.

Using wireless sensor networks (WSNs) in delay and reliability critical environments is highly desired due to their unique advantages such as low cost, ease of deployment, and redundancy. However, successful deployment of resource-limited WSNs in such applications requires strict quality-of-service (QoS) provisioning techniques to meet the desired latency and reliability targets of those applications. Implementation of QoS techniques in WSNs is significantly challenging since WSNs have been initially devised for low-data-rate non-real-time applications. Therefore, WSN designers and developers resort to different cross-layer interaction and optimization techniques to provision QoS in WSNs. In this paper, we present a survey on the state of the art of cross-layer QoS approaches in wireless terrestrial sensor networks to achieve delay and reliability bounds in critical applications. Our paper provides a unique classification of cross-layer QoS approaches in WSNs that allows surveying a large amount of studies with utmost clarity. Furthermore, we highlight the main challenges of implementing QoS protocols in WSNs and present an overview of QoS-aware WSN applications.

Sensor networks are an apt amalgamation of sensing, processing and communication. These networks are formed using tiny inexpensive sensor nodes which have the attributes of low processing power and short radio ranges. They steer themselves to numerous applications and at the same instance, encounter stark energy constraints and face scarce memory resources. The discerning personas of sensor networks also have a direct influence on the hardware design of these nodes. Innumerable hardware platforms like Crossbow, Intel, and IvMote have been fabricated to examine the ideas of the research community and to implement applications in all arenas of science and technology. With so many applications designed in this area, security issues are of paramount importance. In this article, security architectures on the two layers of the network stack—link layer and network layer have been surveyed. The paper surveys the various security requirements for designing a wireless sensor network discussing the architecture of the protocols in comparison with the security primitives of IEEE 802.15.4 standard for wireless sensor network (Shon and Choi in Towards the implementation of reliable data transmission for 802.15.4-based wireless sensor. Ubiquitous intelligence and computing, 5061. Lecture notes in computer science, 363–372, 2008). The paper examines TinySec (Karlof et al. in TinySec: a link layer security architecture for wireless sensor networks. In: Proceedings of the 2nd international conference on embedded networked sensor systems, 2004) a standard protocol used in TinyOS; the operating system deployed in sensor networks; and C-Sec (Moh’d et al. in C-Sec: energy efficient link layer encryption protocol for wireless sensor networks. In: Proceedings in consumer communications and networking conference (CCNC), 2012) at the link layer and MiniSec (Luk et al. in iniSec: a secure sensor network communication architecture. In: Proceedings of the 6th international conference on information processing in sensor networks (IPSN ‘07), New York, 2007) and MoteSec-Aware (Tsou et al. in IEEE Trans Wirel Commun 12(6):2817–2829, 2013) at the network layer. The survey focusses on the vulnerabilities dealt by each protocol, their challenges with respect to energy consumption, scalability and availability. It also highlights the challenges that the protocols have not been able to handle because of resource restrictions. It also projects some future research directions in the area of security.

The thesis deals with the design of intelligent household environment monitoring equipment by the use of ZigBee technology. The system design takes STC12c5a60s2 single-chip microcomputer as the core module of data acquisition terminal. It is a ZigBee-based wireless sensor network acquisition system with low complexity, low power consumption and low cost. The sensor data display capabilities are realized through the single-chip microcomputer. The design mainly consists of the ZigBee wireless sensor network, a single-chip computer and a display device, with the single-chip computer as its core controller. The ZigBee chip CC2530 builds a wireless network for the core, carries temperature/humidity sensors, smoke sensor and infrared sensing devices, which constitute a complete environmental data acquisition system. Introduction With the constant development of wireless telecommunication technology, wireless sensor network has expanded from the earlier military field to industry, science and medicine and is playing an increasingly important role [1]. Wireless sensor network data acquisition technology has evolved from simplification to integration and networking. The ZigBee is a wireless network technology which is a low rate personal area. It’s suitable for such occasions which not amount of data communication, relatively low data transmission speed, a high degree of data security and low power consumption [2]. The thesis deals with the indoor environment monitoring of intelligent households. The sensor network tests the data and the tested data are sent to the acquisition terminal wirelessly. The acquisition terminal analyzes data packet, extracts valid data and displays them on LED 12864. System Design Layout and Device Choice 1. System Framework Layout The system mainly consists of acquisition terminal and sensor network. The whole structure is illustrated in Fig. 1. The acquisition terminal uses a core controller STC12c5a60s2 single-chip computer which is 8-Bit, low-power-consumption and manufactured by domestic corporations. The computer communicates with the coordinator through the serial port. The coordinator ZigBee receives data sent from wireless acquisition node. The core controller analyzes the collected data, extracts valid data and displays them on LCD12864. The sensor network consists of ZigBee node merging sensors.