Autonomous Sensor Nodes Research Articles

Smart Wireless Climate Sensor Node for Indoor Comfort Quality Monitoring Application

The indoor environment climate should be controlled by continuously maintaining the temperature and relative humidity to achieve thermal comfort. A monitoring system of both parameters is the first step to improving indoor comfort quality. This paper presents a smart wireless climate sensor node for indoor temperature and humidity monitoring with a powering strategy and design approach for autonomous operation. The data logging results are sent to the cloud using Internet of Things protocol for thermal comfort monitoring and analysis. The monitoring and analysis results are useful to monitor and control the indoor thermal comfort condition for room occupants. A sensor node was designed that includes a low-power mode and compact size features. It consists of a built-in AVR-based microcontroller, a temperature and humidity sensor, and a wireless module with a supercapacitor as the power storage. A low-power algorithm and Internet of Things system were implemented to reduce the total energy consumption as low as possible during operation while improving the thermal comfort quality. This developed sensor node has a small error for temperature, and relative humidity sensed values resulting from calibration. At the same time, it also consumes low power for one cycle of data acquisition. The device was integrated with an Internet of Things monitoring system to monitor indoor thermal comfort in the field experiment. The experiment results showed that the indoor temperature and relative humidity were measured and recorded in the range of 25–30 °C and 30–40%, respectively. This prototype is a preliminary design to achieve an autonomous sensor node with a low-power energy consumption goal. Thus, with this feature, the developed sensor node has potential to couple with a micro energy harvester module toward a fully autonomous active node in further development.

Energy Autonomous Wireless Sensor Nodes for Freight Train Braking Systems Monitoring.

Nowadays, railway freight transportation is becoming more and more crucial since it represents the best alternative to road transport in terms of sustainability, pollution, and impact on the environment and on public health. Upgrading the potentiality of this kind of transportation, it would be possible to avoid delays in goods deliveries due to road accidents, traffic jams, and other situation occurring on roads. A key factor in this framework is therefore represented by monitoring and maintenance of the train components. Implementing a real time monitoring of the main components and a predictive maintenance approach, it would be possible to avoid unexpected breakdowns and consequently unavailability of wagons for unscheduled repair activities. As highlighted in recent statistical analysis, one of the elements more critical in case of failure is represented by the brake system. In this view, a real time monitoring of pressure values in some specific points of the system would provide significant information on its health status. In addition, since the braking actions are related to the load present on the convoy, thanks to this kind of monitoring, it would be possible to appreciate the different behavior of the system in case of loaded and unloaded trains. This paper presented an innovative wireless monitoring system to perform brake system diagnostics. A low-power system architecture, in terms of energy harvesting and wireless communication, was developed due to the difficulty in applying a wired monitoring system to a freight convoy. The developed system allows acquiring brake pressure data in critical points in order to verify the correct behavior of the brake system. Experimental results collected during a five-month field test were provided to validate the approach.

Development of a Self-Sufficient LoRaWAN Sensor Node with Flexible and Glass Dye-Sensitized Solar Cell Modules Harvesting Energy from Diffuse Low-Intensity Solar Radiation

This paper aims to demonstrate the viability of energy harvesting for wide area wireless sensing systems based on dye-sensitized solar cells (DSSCs) under diffuse sunlight conditions, proving the feasibility of deploying autonomous sensor nodes even under unfavorable outdoor scenarios, such as during cloudy days, in the proximity of tall buildings, among the trees in a forest and during winter days in general. A flexible thin-film module and a glass thin-film module, both featuring an area smaller than an A4 sheet of paper, were initially characterized in diffuse solar light. Afterward, the protype sensor nodes were tested in a laboratory in two different working conditions, emulating outdoor sunlight in unfavorable lighting and weather to reconstruct a worst-case scenario. A Li-Po battery was employed as a power reserve for a long-range wide area network (LoRaWAN)-based sensor node that transmitted data every 8 h and every hour. To this end, an RFM95x LoRa module was used, while the node energy management was attained by exploiting a nano-power boost charger buck converter integrated circuit conceived for the nano-power harvesting from the light source and the managing of the battery charge and protection. A positive charge balance was demonstrated by monitoring the battery trend along two series of 6 and 9 days, thus allowing us to affirm that the system’s permanent energy self-sufficiency was guaranteed even in the worst-case lighting and weather scenario.

Wide-Range Light Harvesting Module for Autonomous Sensor Nodes

A large number of autonomous devices is nowadays supported by renewable and green energy sources. A vital sub-circuit in such systems is the power converter circuit, which should efficiently transform and store the available energy. In order to obtain the maximum efficiency under varying energy conditions, various maximum power point tracking (MPPT) methods are used. In this work a complete harvesting module with battery management and MPPT is presented, suitable for a plethora of autonomous applications. A novel, low-complexity and ultra-low power consumption design is proposed, which offers very wide operating voltage and power range with high MPPT efficiency and very low power consumption. It can be combined with different harvesters, such as thermoelectric generators or photovoltaic panels and is able to work under widely varying energy conditions. As supported by experimental results, the proposed module covers a very wide working input power range, from 40 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{W}$ </tex-math></inline-formula> up to 4 W, as well as a very wide input voltage range, from 650 mV up to 2.8 V with 96.5% average MPPT efficiency and a total power consumption of 3.9 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{W}$ </tex-math></inline-formula> at 3.6 V. The module relies on an embedded ultra-low power microcontroller unit (MCU) to perform the power management and MPPT operations, which can also be used for extra tasks (e.g., sensor reading). Using the proposed module, an autonomous sensor node was built, able to acquire acceleration measurements, and wirelessly communicate with a remote user in order to send an alert or stream the acquired sensor data in real time.

Robust Node Localization with Intrusion Detection for Wireless Sensor Networks

Wireless sensor networks comprise a set of autonomous sensor nodes, commonly used for data gathering and tracking applications. Node localization and intrusion detection are considered as the major design issue in WSN. Therefore, this paper presents a new multi-objective manta ray foraging optimization (MRFO) based node localization with intrusion detection (MOMRFO-NLID) technique for WSN. The goal of the MOMRFO-NLID technique is to optimally localize the unknown nodes and determine the existence of intrusions in the network. The MOMRFO-NLID technique encompasses two major stages namely MRFO based localization of nodes and optimal Siamese Neural Network (OSNN) based intrusion detection. The OSNN technique involves the hyperparameter tuning of the traditional SNN using the MRFO algorithm and consequently increases the detection rate. In order to assess the enhanced performance of the MOMRFO-NLID technique, a series of simulations take place and the results reported superior performance compared to existing techniques interms of distinct evaluation parameters.

A Novel Dual-band Ambient RF Energy Harvesting System for Autonomous Wireless Sensor Node Application

This paper presents a novel dual-band ambient Wi-Fi energy harvesting system for an autonomous wireless sensor node (AWSN) which operates independently without other external power source. While conventional wireless sensor nodes employing batteries with limited lifespans, an AWSN is supplied by harvested energy and does not require frequent battery replacement. Due to that reason, research on the energy harvesting aspect of AWSNs has been carried out intensively in recent years. By optimizing the matching network, the proposed ambient Wi-Fi energy harvesting system achieves a relatively good efficiency in dual-band at 2.45 GHz and 5.8 GHz. The efficiency reaches a peak at 47.45 % and 42 % at 2.45 GHz and 5.8 GHz, respectively. The proposed idea is numerically and experimentally demonstrated with the Wi-Fi source in building.

Task Scheduling for Energy-Harvesting-Based IoT: A Survey and Critical Analysis

The Internet of Things (IoT) has important applications in our daily lives, including health and fitness tracking, environmental monitoring, and transportation. However, sensor nodes in IoT suffer from the limited lifetime of batteries resulting from their finite energy availability. A promising solution is to harvest energy from environmental sources, such as solar, kinetic, thermal, and radio-frequency (RF) waves, for perpetual and continuous operation of IoT sensor nodes. In addition to energy generation, recently energy harvesters have been used for context detection, eliminating the need for conventional activity sensors (e.g., accelerometers), saving space, cost, and energy consumption. Using energy harvesters for simultaneous sensing and energy harvesting enables energy positive sensing-an important and emerging class of sensors, which harvest more energy than required for context detection and the additional energy can be used to power other components of the system. Although simultaneous sensing and energy harvesting is an important step forward toward autonomous self-powered sensor nodes, the energy and information availability can be still intermittent, unpredictable, and temporally misaligned with various computational tasks on the sensor node. This article provides a comprehensive survey on task scheduling algorithms for the emerging class of energy harvesting-based sensors (i.e., energy positive sensors) to achieve the sustainable operation of IoT. We discuss inherent differences between conventional sensing and energy positive sensing and provide an extensive critical analysis for devising revised task scheduling algorithms incorporating this new class of sensors. Finally, we outline future research directions toward the implementation of autonomous and self-powered IoT.

Precision blade deflection measurement system using wireless inertial sensor nodes

AbstractStructural health monitoring on wind turbine blades is a great enhancement for operational safety and failure avoidance. Blade deflection is a key parameter, which is a function of blade geometry and material properties. The absolute blade deflection is affected by wind load, gravitational, and centrifugal forces and must exceed neither material stress limits nor tower clearance. In this paper, we introduce a novel method for real time reconstruction of blade movement using inertial measurement units (IMUs) located at defined positions along the blade. An algorithm is introduced that combines IMU measurements and a priori information of the fundamental blade mode shapes to accurately reconstruct the blade movement. A low‐power wireless sensor node for blade deflection monitoring is presented. The autonomous sensor node is equipped with an IMU together with a low‐power wireless transceiver and powered by a compact translational electromagnetic energy harvester. Sufficient energy is harvested each rotor revolution for continuous measurement data streaming within the wind turbine's operating range. A data stream of six‐axis IMU measurements enables real time, three‐dimensional reconstruction of the entire blade movement in the back end positioned in the tower. The reconstruction of blade tip deflection is possible even under high wind turbulences with a minimum accuracy of 0.22 m for an onshore 5 MW and 0.58 m for an offshore 15‐MW reference turbine. The complete system has been tested thoroughly under conditions similiar to a real wind turbine. Realistic stimulation of the reconstruction algorithm is performed by means of OpenFAST simulations.

An Autonomous Wireless Sensor Node Based on Hybrid RF Solar Energy Harvesting

The widespread deployment of the Internet of Things (IoT) requires the development of new embedded systems, which will provide a diverse array of different intelligent functionalities. However, these devices must also meet environmental, maintenance, and longevity constraints, while maintaining extremely low-power consumption. In this work, a batteryless, low-power consumption, compact embedded system for IoT applications is presented. This system is capable of using a combination of hybrid solar and radiofrequency power sources and operates in the 900 MHz ISM band. It is capable of receiving OOK or ASK modulated data and measuring environmental data and can transmit information back to the requester using GFSK modulated data. The total consumption of the system during its sleep state is 920 nW. Minimum power required to operate is −15.1 dBm or 70 lux, when using only radiofrequency or solar powering, respectively. The system is fully designed with components off the shelf (COTS).

NODE BASED CLONE ATTACK DETECTION IN STATIC WIRELESS SENSOR NETWORKS

Wireless Sensor Network (WSN) is a combination of autonomous sensor nodes and used to monitor various physical conditions. Static and mobile are two types of WSN. In static WSN the sensor nodes do not alter their positions after deployment. Due to the security constraints, WSN is vulnerable to various types of attacks. In that, Clone attack is the most dangerous attack on WSN. In Clone attack an adversary physically captures a sensor node. It reprograms the detained node and generates many clone nodes. The real nodes and clone nodes are installed in the sensor field, so clone node identification is a difficult task. The new protocol proposed to identify the clone nodes in the static WSN called as Node Based Clone Attack Detection (NBCAD) protocol. This protocol detects the clones in a efficient manner compare with SET and RED protocols. The advantage of proposed NBCAD protocol include high clone detection ratio, minimum communication overhead, minimum end-to-end delay, minimum latency time and high throughput.

Design of a solar energy harvesting system for supplying energy to an autonomous wireless sensor node

Introduction: This paper is the product of the research “Generation of a modular electronic platform for the conformation of a WSN” developed in the EAFIT University in 2019.&#x0D; Problem: Wireless Sensor Networks (WSNs) are used as a technology of information and communication (TIC) to automate processes. Its implementation is considered non-efficient, because of their high cost concerning to the batteries replacement that the nodes conforming the WSN, require.&#x0D; Objective: The objective of the research is to develop more efficient solar energy harvesting systems that can guarantee an average performance of the wireless sensor node at a low cost.&#x0D; Methodology: Here we present the design and the implementation of a solar energy harvesting system that integrates a buck converter, a maximum power point tracking (MPPT) control, and a wireless sensor node. Besides, we do measures of voltage at the output of the buck converter and estimation of energy autonomy in the wireless sensor node.&#x0D; Results: Autonomous operation with the solar energy harvesting system was rich for the node sending packages each 20 min.&#x0D; Conclusion: This article presented a solar energy harvesting system with the implementation of an MPPT control.&#x0D; Originality: Through this research, parameters of the MPPT control are formulated for the first time for the solar energy harvesting system design, based on the duty cycle limits.&#x0D; Limitations: The availability of the devices used in the implementation of the proposed design.

A Self-Sustained Current Sensor for Smart Grid Application

Along with the ever-increasing attraction of the internet of things, self-sustainable smart sensor is receiving more and more attention. However, in some industrial sensing applications, such as the monitoring system of the transmission line in power grid, there are still a lot of critical technical issues that remain to be addressed. On the one hand, the power issue has long been an obstacle of the sensors in power grid because the routine maintenance in this case is almost impossible considering its high cost. On the other hand, highly integrated current sensing techniques with large linear range for measuring the transmission current in power line are still limited. To date, in the power grid, autonomous current sensor nodes with free-standing designs are in great demand. In this article, a complete solution for addressing these two issues has been proposed. First, a magnetic energy harvester that can scavenge the ambient power-frequency magnetic field around the transmission line is proposed. The proposed electrodynamic design is based on nonlinear resonance, which is demonstrated to have a higher power density. The power density of the prototype can be as high as 3.42 mW/cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> (tested at merely 3 Oe applied magnetic field). Second, a power management circuit is specially designed for the energy harvester. The minimum input voltage of the circuit can be as low as 0.33 V. Finally, an anisotropic magnetoresistance (AMR) sensor head with large linear range is customized for sensing the current in power grid. The largest linear range of the AMR sensor can be as large as ±170 Oe. The specially designed sensing system can be a promising solution to realize the new generation of self-sustainable current sensor network in power grid.

Tapered nonlinear vibration energy harvester for powering Internet of Things

The lack of a sustainable power source to substitute batteries for long-term applications limits the widespread deployment of wireless sensor nodes in this era of the Internet of Things. Conventional linear Vibration Energy Harvesters are inefficient in converting ambient mechanical energy into usable electrical energy owing to their narrow frequency bandwidth when harnessing mechanical energy that is spread over a wide range of frequencies. In this work, we design, develop and demonstrate high power density nonlinear wideband energy harvesters using novel tapered spring architectures in an autonomous wireless sensor node system. These spring structures exhibit a nonlinear restoring force arising from the atypical stress distribution that can be additionally tuned by changing the taper-ratio in the structure. We investigate different tapering designs in order to achieve optimal spring hardening nonlinearities. This nonlinearity aids in widening the operable bandwidth, making the harvesters suitable for scavenging energy from real-world broadband vibrations. We obtain power densities of the order of 2660 μW/cm3g2 in the nonlinear energy harvester, outpacing most contemporary energy scavengers. We present a modified Perturb and Observe algorithm that allows tracing of the maximum power point in the context of non-stationary vibration conditions. We use the fabricated nonlinear device to power a wireless sensor node that reports on vital physical parameters (humidity, temperature), thereby enabling a resilient remote data acquisition system. This demonstrates the potential of our design to provide a sustainable energy source for platforms within the Internet of Things.

Energy Harvesting Technologies for Structural Health Monitoring of Airplane Components-A Review.

With the aim of increasing the efficiency of maintenance and fuel usage in airplanes, structural health monitoring (SHM) of critical composite structures is increasingly expected and required. The optimized usage of this concept is subject of intensive work in the framework of the EU COST Action CA18203 “Optimising Design for Inspection” (ODIN). In this context, a thorough review of a broad range of energy harvesting (EH) technologies to be potentially used as power sources for the acoustic emission and guided wave propagation sensors of the considered SHM systems, as well as for the respective data elaboration and wireless communication modules, is provided in this work. EH devices based on the usage of kinetic energy, thermal gradients, solar radiation, airflow, and other viable energy sources, proposed so far in the literature, are thus described with a critical review of the respective specific power levels, of their potential placement on airplanes, as well as the consequently necessary power management architectures. The guidelines provided for the selection of the most appropriate EH and power management technologies create the preconditions to develop a new class of autonomous sensor nodes for the in-process, non-destructive SHM of airplane components.

Self-sustained autonomous wireless sensing based on a hybridized TENG and PEG vibration mechanism

Autonomous wireless sensor nodes (WSN) for information acquisition and status monitoring, play an important role in the boom area of the internet of things (IoT) and industry 4.0. Self-sustained power supply is an important pursuit in massive practical applications but yet to be developed. Here we propose a novel hybrid piezoelectric generator (PEG) and triboelectric nanogenerator (TENG) to form a novel self-sustainable WSN. The PEG consisting of a hinged-hinged PZT bimorph and two T shaped proof mass, has an output power of 6.5 mW excited in 25 Hz at 1.0 g. PEG also shows broadband characteristics thanks to the impact of the TENG and tunable frequency due to the axial force. 30 serial LEDs in sine vibration and 20 serial LEDs in shock vibration are lighted up with the proposed double voltage rectifier circuit by PEG, which can serve as alarming signals in vibration and drop monitoring. The triboelectric accelerometer shows good linearity with a sensitivity of 15 V/g in 0–1.5 g with an optimized gap of 1.5 mm. After low power design, Arduino nano and RF transceiver can be sustainably powered by PEG, and send the TENG acceleration signal wirelessly by Zigbee. A VR train monitoring demonstration has been conducted showing the great prospect of the self-sustainable WSN in harsh environments. A novel hybridized piezoelectric generator (PEG) and triboelectric nanogenerator (TENG) vibration mechanism is proposed to achieve self-sustained autonomous wireless sensor node (WSN). A VR train monitoring demonstration has been conducted showing the great prospect of the self-sustainable WSN in harsh environments. • A novel hybridized PEG and TENG vibration mechanism is proposed to achieve a self-sustained autonomous WSN. • Both impact-induced broadband behavior and axial force-induced tunable frequency are achieved in PEG. • A VR train monitoring demonstration shows the great prospect of the self-sustainable WSN in remote and harsh environments.

Optical Wake-Up From Power-Off State for Autonomous Sensor Nodes

Wireless sensor nodes spend most of their time in standby mode and wake up periodically to send measurement data. Typically, a radio-frequency antenna is coupled with an amplifier to provide this wake-up function; together, these two elements recognize instances of radio signal activation. Even during standby operation, the sensor node utilizes a certain base amount of energy, which can be critical when using an energy-harvesting source. In this study, we propose a novel optical approach to the wake-up function for autonomous sensor nodes, which employs a solar cell as the wake-up signal detector. A bright light flash coming from another node or a smartphone hits a solar cell and activates the sensor node. Unlike photodiodes or RF-antennas, solar cells do not require any additional energy to detect such a signal. Therefore, the proposed electrical circuit allows the sensor node to wake-up from a complete power-off state. The solar cell of the novel wake-up receiver has an area of sensitivity of 8 mm × 10 mm. The wake-up signal can be recognized from a maximum distance of 25 cm at a range of ambient illumination from 0 - 1600 lx with a transmitter optical power of 20 mW. In the power-off state, the power consumption of this novel design is the lowest of all existing off-the-shelf wake-up receivers: 248 pW at 0 lx and 627 nW at 1600 lx.

A three-tier cluster-based routing protocol for mobile wireless sensor networks

Background/Objectives: Based on the recent advances in the area of wireless networking, computing, and storage devices, Wireless Sensor Networks (WSN) has emerged as an evolving and future-enabled technology in recent decades. The objective of the research work is to design, analyse, and evaluate the performance of A Three-Tier Cluster-Based Routing Protocol for Mobile Wireless Sensor Networks. Methods/Statistical analysis: The proposed protocol is based on autonomous sensor nodes, distributed techniques on cluster development; cluster heads collected at random, multi-hop routing method, and transferring the data towards the base station used by the assistance of MDC maximum residual energy LEACH. Findings: WSN is used globally in different forms of networking technologies; these systems come with the ability to be applied worldwide at an unrivaled scale and to add a consistent viewpoint to production. Routing protocols in these networks act as middleware, which is responsible for enhancing the network performance with less energy consumption and the cluster-based routing protocol is a massive solution to improve node’s energy efficiency and reliability of data toward the base station. Moreover, the simulation results showed that the proposed protocol achieves not only better network lifetime and data reliability but also decreased energy dissipation of the sensor nodes when compared with prominent WSN cluster-based routing protocols. Novelty/Applications:The main outcomes of MDC maximum residual energy LEACH are: Minimize the energy consumption of sensor nodes, Enhance the overall network lifetime, Resolve communication (energy and routing) holes issues, Maintain data reliability, and finally reach tradeoff between energy efficiency and latency in terms of End-to-End and channel access delays. This proposed protocol has been substantially applicable in an extensive variety of environmental and civil surveillance applications. Keywords: Wireless sensor network; mobile data collector; three-tier architecture; data gathering method; cluster-based routing

AMPC: A Lightweight Hybrid Cryptographic Algorithm for Wireless Sensor Networks

Wireless sensor network (WSN) is a group of several autonomous sensor nodes attached to each other. Wireless sensor networks are commonly used in a lot of applications and are expected to have a cheap deployment cost. The network of sensors continues to grow aiding the need of the system. Due to that, sensors become vulnerable to attacks and need strong security mechanism. To strengthen the security of data which are transmitted through sensors in WSN, different cryptographic schemes are used. As WSN has limited energy source, therefore, complex cryptographic algorithms may require excessive computational time which not only make the data transmission slow but the life time of sensor network will be significantly affected. To overcome these challenges a new hybrid cryptographic scheme, AES and Modified Playfair Cipher (AMPC), is introduced in this paper.

Analysis of security and energy efficiency for shortest route discovery in low‐energy adaptive clustering hierarchy protocol using Levenberg‐Marquardt neural network and gated recurrent unit for intrusion detection system

AbstractWireless sensor network (WSN) is a collection of a huge number of autonomous sensor nodes having capabilities such as sensing, processing, and manipulation. In any WSN, routing protocols are the backbone for performing all type tasks such as sensing, controlling, and transmission of packets in ubiquitous environment. In this article, a LEACH protocol with Levenberg‐Marquardt neural network (LEACH‐LMNN) is considered to analyze the overall network lifetime. The aim of LEACH‐LMNN protocol comprises two parts: selection of cluster head node using LMNN approach and the second part is to locate the shortest path from the cluster‐head node to base‐station node adopting various route discovery algorithms, that is, breadth‐first search, Bellman‐Ford, and Dijkstra. The simulation result shows that the LEACH‐LMNN protocol with the Dijkstra shortest path algorithm outperforms other route discovery algorithms. In addition to this, this work also analyzes normal and anomaly detection based on intrusion detection system in wireless sensor networks using gated mechanism, that is, long short‐term memory (LSTM) and gated recurrent unit (GRU) in deep learning models. The proposed model achieves the highest detection rate of 97.84% for GRU and 97.85% for LSTM as well as improves the false positive rate (FPR) of 5.87% and 3.88% FPR for GRU and LSTM, respectively.

IADF security: insider attack detection using fuzzy logic in wireless multimedia sensor networks

Wireless multimedia sensor networks (WMSNs) consist of spatially distributed, autonomous sensor nodes that monitor physical or environmental conditions. WMSN networks, in general, are prone to insider attacks like node replication attacks, where a malicious node replicates itself as an insider node, which may lead to a situation where a non-authentic node becomes a rightful part of the network. Insider attacks are not detectable with classic cryptographical techniques. Many WMSN applications require a dedicated on-demand algorithm to detect the insider attacker in the system without any prior knowledge of the system. This paper proposes a new security scheme, called the insider attack detection using fuzzy logic (IADF). This security scheme uses the fuzzification of six parameters present in a wireless multimedia sensor node categorized as network and physical parameters. Physical parameters used are received signal strength, transceiver range and residual energy. Network parameters used include packet delivery ratio, forwarding delay and transmission rate. The fuzzy approach makes the IADF algorithm flexible and scalable. Simulation results show that the IADF algorithm can predict malicious nodes with a higher prediction rate and higher detection accuracy.