Al-Rafidain Engineering Journal (AREJ)

This paper presents a security paradigm for edge devices to defend against various internal and external threats. The first section of the manuscript proposes employing machine learning models to identify MQTT-based (Message Queue Telemetry Transport) attacks using the Intrusion Detection and Prevention System (IDPS) for edge nodes. Because the Machine Learning (ML) model cannot be trained directly on low-performance platforms (such as edge devices),a new methodology for updating ML models is proposed to provide a tradeoff between the model performance and the computational complexity. The proposed methodology involves training the model on a high-performance computing platform and then installing the trained model as a detection engine on low-performance platforms (such as the edge node of the edge layer) to identify new attacks. Multiple security techniques have been employed in the second half of the manuscript to verify that the exchanged trained model and the exchanged data files are valid and undiscoverable (information authenticity and privacy) and that the source (such as a fog node or edge device) is indeed what it it claimed to be (source authentication and message integrity). Finally, the proposed security paradigm is found to be effective against various internal and external threats and can be applied to a low-cost single-board computer (SBC).

Industrial IoT (Industrial IoT) is a new promising technology which can be used to increase the amount of productions with high qualities. Industrial IoT technologies guarantee full control to the processes remotely through the internet which can reduce the number of workers in the field. As a result, this can reduce the percentage of worker injuries and accidents in addition to the total costs. The Industrial IoT systems are attractive targets to attackers. For this reason, these systems require high levels of security since such levels have direct effects on physical devices which may be dangerous on human life and safety. To   guarantee high level of security, a combination between Information Technologies (IT) and Operation Technologies (OT) with new innovative methods should take place. In this paper, many new technologies and security methods are reviewed with their possible attacks in order to provide Industrial IoT infrastructure designers with the required information to take them into consideration. Also, differences and convergences between both classical Information Technology (IT) and operational Technology (OT) and their relations to the Industrial IoT systems are investigated with the possible attacks on each layer of the IT and the OT.

In a larger sense, "green computing" refers to strategies and procedures for creating, utilizing, and disposing of computer resources in three ways: maintaining total computing performance, minimizing the impact on the environment, and maintaining overall computing performance. This entails using less dangerous materials, getting the most usage possible out of a product while using the least amount of energy possible, as well as making old items and the garbage more reusable, recyclable, and biodegradable. Many businesses are making efforts to lessen the negative effects of activities on the environment. The framework Convention on Climate Change of the United Nations (UNFCC)is a global environmental agreement whose goal is to keep greenhouse gas emissions stable to a degree that would prevent adverse anthropogenic interference with the environment. Sustainable development entails growth that doesn't jeopardize the needs of coming generations. That is achieving human development goals while protecting the ecosystems and natural resources that are essential to civilization. The relevance of green computing for sustainable development is emphasized in this paper's assessment of many significant recent studies on the subject.

The traditional centralized cloud computing paradigm confronts several problems, including a lack of capacity, high latency, and network failure, due to the rapid expansion of IoT (Internet of Things) applications. Fog Computing brings cloud computing and IoT devices closer to addressing these issues. Instead of transferring IoT data to the cloud, the Fog allows local processing and storage of IoT data in IoT devices. Fog Computing offers services with a quicker response time and higher quality than the cloud. Therefore, Fog Computing may be considered the greatest option for enabling the IoT to provide efficient and secure services to many IoT users. In this paper, we define the term "Fog Computing," examine its architecture  and list its features. We also talk about other related work and emphasize it.

The  theory of automata combines ideas from engineering, linguistics, mathematics, philosophy, etc. The Entscheidungsproblem asks if it is possible to design a series of steps that replaces a mathematician. An automaton is an abstract machine that processes data. C. Shannon's theory is today's most popular despite having no relationship with the other. The Kt system is called "minimal" because it makes no assumptions about the structure of time. In LKt, we have four monary temporal operators, F, P, G and H, which are mutually interdefinable. Interdefinability means that we will pass logic in the future is the same as saying I will never fail logic,  interpreting not passing logic as failing logic. The minimal system syntax of temporal logic introduces operators that have the property of being defined in terms of others. Modal logic studies the reasoning that involves the use of expressions "necessarily" and "possibly". In this article, we will represent through a finite automaton the temporal logic formula Fp. It allows us to see an acceptance pattern for Fp by considering two variables: p and q. Kt's axiomatic system of time expresses the idea that both the present and the past are fixed, if it has always been in the past that it will be some time in the future that p is now. No philosophical argument supports deterministic time flow; the logic of time must be open.Temporal logic has revived many old problems, from the Megaric-Stoics to the minimal system of temporal logic. Our work suggests that the future operators of system Kt follow an evaluation pattern, but we must be cautious because this pattern can only apply to models whose time flow is based on instants and precedence relations.

Wireless communication network (WCN) technologies are charming solutions to bolster the conventional electrical substations with the intention of take the fashion of smart substation such as reduction in equipment, minimize the maintenance costs, flexibility, and expansion. However, the harsher challenge facing WCN employing in the electrical substation is the real time protection of substation automation system (SAS) for the high voltage devices in terms of the latency and the reliability in particular the substations of old topologies. This work suggests WCN including special types of the intermediate devices (Switched-Access Points (S-AP) and Multi Wireless Domain- Access Point (MWD-AP)) to address the expected packets congestion by creating independent wireless channels domains offering wireless channels reliability in such network topology that deals with real time data traffic (RT) and the non-real time data traffic (NRT). Riverbed modeler is adopted to simulate the model of the electrical substation network due to the rich tools of communication networks in term of industry environment. The results indicate, the suggested WCN can handle the hard real time requirements of protection from latency and data reliability points of view in case of basic capacity of 802.11a/n standards at the level of ≤ 4 msec and high data reliability.

Chatbots, or machine based conversational systems, have become popular in recent years in a variety of applications. Chatbots are intelligent technologies that employ Artificial Intelligence (AI) to converse with humans in their natural languages. Chatbot's primary function is to interpret user's questions and respond with the most convenient intelligent and natural responses. In a number of the world's most generally spoken languages, chatbots appear to be quite successful; however, Arabic chatbots have not yet attained the predicted degree of success. Many academics have recently sought to bridge the gap in the implementation of Arabic chatbots by overcoming the complicated linguistic Arabic language features. This survey reviews the chatbots, their categories and implementation techniques. It also, presents some challenges that face the developer of Arabic chatbots due to rich complex properties of Arabic language. Then, most of published chatbot researches that deal with Arabic language are highlighted. Finally, a table of comparison among the mentioned Arabic chatbots is presented. The study concludes that, all the present AI based Arabic chatbots are developed in retrieval mode, and that Arabic chatbot literature is scarce in comparison to that in many other languages.

Automatic Speech Recognition (ASR) is a tough task, with the existence of related noise and high unpredictability in a speech presenting the most severe problems. Especially with regard to the noise of speech impairments, whether due to disability or mispronunciation in children. Extraction of noise-resistant features to compensate for speech degradation due to noise impact has remained a difficult challenge in the last few years. This research investigated the impact of different wavelet generations for extracting speech features, then test the produced dataset from each technique with two types of deep learning techniques: deep long short-term memory (LSTM) and hyper deep learning model convolutional neural network with long short-term memory (CNN-LSTM). The result shows that the deep long short-term memory of MFCC has reached 93% as an accuracy while in the hyper deep learning model of CNN-LSTM the accuracy of MFCC was 91%, as the highest recorded accuracy which proves that MFCC would be the best feature extraction technique for our developed dataset.

To highlight issues and challenges of the Load Balancing Algorithm (LBA) in the context of cloud computing. The authors of this work discussed load balancing and the load balancing problems in cloud computing, how to solve them, the basic techniques used to maintain load over the cloud, and the benefits and drawbacks of these algorithms. Furthermore, the static and dynamic load balancing strategies are compared. Load balancing methods in the cloud for data centers must avoid VM overload/low load, which is a challenge in cloud computing. Load balancing mechanisms aid in the management of workloads. The primary goal of load balancing among machines is to spread workloads and computing resources across one or more servers while lowering energy consumption and maximizing resource usage. Cloud computing is a type of computing in which scalable resources are made available on-demand and are frequently virtual, as in an online service. For a variety of reasons, including cost saving, speed, efficiency, performance, and security, cloud computing has recently become a popular choice for individuals and enterprises. Cloud computing uses the Internet to deliver a variety of services to a company's computers and devices. These resources can include data storage, databases, servers, networks, and software, among other tools and applications. In this paper, developers and researchers must design and construct a load balancer e for parallel and distributed cloud systems.

One of the most important challenges facing U-Net architecture performance is the method design of its components and how to choose the suitable hardware computing device to deal with the training labelled datasets.  Convolution is the most process that requires computations and memory costs, which is needs to minimize. Thus, one of the suitable selection is to change the type of the convolution. Other suggested solutions are to reduce the size of image,    number of bits, and, stride value, in addition to number of filters, and image batches. Therefore, in this paper the roofline model will used as performance guide in analyzing the FLOPs and the memory bandwidth boundaries of a U-Net model with different configurations. The cost has been assessed with compared to the limitation of three computing devices, GPU230MX, GPU940MX and GPU2060rtx super. 128 × 128 image dataset has been used during the U-Net cost-performance evaluation process. Based on the analysis, the evaluation results show that the solution that achieves a balance between memory and computations is to implement a U-Net model in parallel using RTX2060 super card with the configurations of batch size is 16, image size of 128×128, number of bits is 32, shared memory management.

The Iraqi political arena has witnessed a dramatic change after the year of 2003. It moved from the dominated republican system to a democratic system. This movement in the political system has affected the situation in Iraq in terms of economic, education, industrial, trading, to mention a few. This paper analyses the Iraqi parliament representatives’ affiliations in terms of their coalitions they formed in the elections. Moreover, this study tries enabling us to deeply understand how the Iraqi parliament representatives are connected to each other and the relations among them. It also provides us with information on how different provinces adopted different coalitions regardless their religion and other tendencies. Several political networks were generated and visualized based on the concepts of complex networks. Each network represents a particular political aspect of the current Iraqi parliament. This study also reveals a new trend of forming coalitions in Iraq and the strategy followed by the representatives in attaching to coalitions. Finally, we believe this is the first kind of work that uses this approach of analysis in understanding the trend of Iraqi politicians.

The precise position control of a DC servo motor is a major concern in today's control theory. This work presents position following and forecast of DC servo engine utilizing an alternate control technique. Control technique is required to limit and diminish the consistent state error. A model predictive controller MPC is utilized to plan and actualize these prerequisites. Two sorts of controlling techniques are presented in this task. The Active Set Method (ASM), the inside point technique (IIP), and have been utilized as controlling strategies. This work distinguishes and depicts the plan decisions identified with a two sorts of controllers and judicious regulator for a DC servo motor. Execution of these regulators has been confirmed through reproduction utilizing MATLAB/SIMULINK programming. As indicated by the recreation results the Comparisons among ASM, IIP. The tuning strategy was increasingly proficient in improving the progression reaction attributes, for example, decreasing the rise time, settling time and most prominent overshoot in Position control of DC servo motor.

Today electricity supplement still has power failures and blackouts due to the lack of automated analysis and the utility's low visibility over the grid. Small and undetected electrical problems can have far-reaching consequences. These failures cause not only high-energy losses, but also costly unscheduled outages, severe injury to employees, and even a fire. Therefore, the monitoring of electrical substations is essential to detect faults and ensure long-term safe operation, safety, protection, and reliability. Internet of things technology provides the possibility of obtaining station data in real-time. In this research, two systems were designed, implemented, and tested in high voltage electric stations. The first part is designed to obtain data on the environmental conditions at the substations, and the important parameters from the transmission lines at the substations in real-time, which help to prevent power outages by relying on engineers who can analyze comprehensively the electrical energy. The system also provides the Automatic Under Frequency Load Shedding ability if the frequency in the stations falls below the normal limit, which contributes to maintain the efficiency and the quality of electrical energy in the substations, and provides protection for the substations. The second part is designed to obtain the values of the parameters that determine the electrical transformers' conditions and monitors the status of the line in terms of switching off and on in real-time at the substations. Thus, these proposed systems are transforming the traditional substations into smart substations. The performance of the system is introduced based on correlation of data and percentage error. The best correlation was for the current data and the least percentage error was for the current. We strongly believed that the proposed system is vesible.

The research aims to address one of the complex problems that may be encountered when generating computer images for three-dimensional (3D) objects, which is the hidden surface detection and elimination. Several methods have been devised, through the last three decades, to solve this problem. However, the most popular methods used widely nowadays are depth or Z-Buffer (ZB) and Binary Space Partition Tree (BSPT). The first method (ZB) is very simple and more general but requires additional memory to store depth values in addition to intensity. On the other hand, (BSPT) method is more complex to implement but requires memory for pixel intensity only. Modelling graphical database in a binary tree make the dealing with parts of the database feasible. This is so important for clipping a part or more of the database when outside the viewing zone. 
The focus of this paper is to study these two methods, design an algorithm to implement each of them. After that a reasonable procedure is to found and applied for testing the performance of each of the two methods using exactly the same graphic load. A step by step increase of this load should be possible so that the behavior of the execution time at different complexity level and on average bases can be reported. The outcome results of the two methods should be compared and a recommendation to use which one of them is to be concluded [1]. Since one of the most popular graphics library which is being used during the last ten years and nowadays is the Open Graphic Library( OpenGL) from(Silicon Graphic Incorporation (SGI)[2], the algorithms of this work are implemented and the related software is carried out using this library with visual C platform.

The IEEE 802.16e standard includes several features that aid data capacity. When dealing with real-time applications such as video conference services, however, it quickly depletes its resources. The quality of the video, on the other hand, is a crucial factor for the user. There is a tradeoff between the video quality and the resources available. In this paper the influence of frame length on video applications was investigated by examining the effect of four frame lengths (5, 10, 15, and 20 mSec) on the Packet Delay Variation, End-to-end packet delay, traffic sent and received with modulation type 64QAM and high quality of video conference application are used. The optimal frame length was found to be 10 milliseconds, with the Packet Delay Variation being the smallest, the Packet End-to-End Delay being the shortest, and the number of received packets being equal to the number of sent packets.

Nowadays, the mobile robot can be seen in different fields of engineering and science. The mobile robot can do some tasks that are so difficult or very risky to be performed by a human. Most of the works currently focus on implementing artificially intelligent algorithms and other algorithms that depend on the behaviour of nature. These approaches have been used in mobile robot navigation along uncertain manner. Mobile robot navigation strategies can be divided into two approaches: the classical approach and reactive approach. The classical approach related to static environment, whiles the reactive navigation is based on an unstructured environment. Path planning is one of the most important parts of the navigation system. In this paper, review and assessment of path planning strategies that can concern with the reactive approach are discussed, because it deal with the problem of dynamic environment.  Numerous reactive methods have been introduced. Most of these presented works were concerned with simulation and a few of them have shown experimental implementation. Many papers tried to make a combination between two algorithms or more to increase the efficiency. It is concluded that reactive algorithms need more learning phases, complex in design, and require large memory storage.

Image Fusion is applied to get back a group of data from two or more than two images and put it into one image to create additional wealthy information and profitable more than any of the input data that led to increase the features and performance of information.  The quality of the resultant data relies on the implementation of the process. Image fusion is excessively utilized in stereo camera fusion, medical application, manufacture process monitoring, electronic circuit design and inspection, complex machine diagnostics and in intelligent robots on assembly lines. This study displays a literature review on different types of algorithm and theories which apply on images. Many quality criteria have debated to do a brief comparison of these methods. The applications of image fusion are showed in this paper.

This paper introduces different topics about Air pollution monitoring based on IoT (internet of things). It describes different methods used for monitoring and measuring Air pollution using different techniques. Some papers discussed Air pollution monitoring using (Arduino uno, Raspberry or ESP8266, PIC microcontroller). All would be presented to improve air monitoring efficiently and to clarify the tools used in each technique giving the differences between one technique and another. Reducing air pollution is necessary for the future, and cities around the world are using technology and smart city initiatives to take on the problem because it is considered as the major environmental risk factor for human health. Air pollution causes heart disease, stroke, chronic obstructive pulmonary disease, lung cancer and acute lower respiratory disease. Therefore, it is important to reduce traffic and output from factories to decrease pollution

The human signature is an important biometric feature that is used to identify human identity. It is essential in preventing falsification of documents in numerous financial, legal, and other commercial settings. The computerized system enters many aspects of our life, security is one of them, continues developing in computer vision and artificial network leads researcher to develop computerized signature recognition. This paper proposed a real-time algorithm for signature recognition. It is based on client and server operation.in which, client agent captures a signature and sends it to the server through the network. The server receives data and performs processing on it. Processing algorithm is based on weightless neural network. It is chosen for its simplicity and few numbers of sample required for training. The algorithm is tested and evaluated and show the ability to process 4.7 images per second.

Every house and workplaces should install electricity energy meter to evaluate the electricity consumption.  Finally of consistently, a large number of us get stressed over the high power bill and it is need to check the energy meter once in a while. In this work a smart electricity energy meter using ESP32 microcontroller which monitor energy through the PZEM-004T at any time and send to the office. Where this PZEM -004T is used for voltage and current measurements. Then the records will send to the office and store in the SQL database and also web page which is used specific IP. The results have been generated using MYSQL and the curves of the values with the time are also plotted using Microsoft Excel 2010. 

The paper presents and discusses how to use some techniques to reduce the effect of error in the weighting signal which is produced from a load cell. The load cell is one of succeful sensors which is used to transform the weight to an electrical signal.  In industry the production of an accurate signal suffers from a problem of noisy environment. Different source of noise like electromagnetic fields from motors, machines, power lines and microwave in addition to humidity and tempreture variations have significant effects on weak electrical signals produced by load cells.Both hardware and software filtering are adopted to reduce the un wanted effects.

Any robot system consists of mechanical and electrical components. . Mostly and with time obsolescence, faults and errors are happen in robot systems lead to work problems. Many years ago, scientist and researchers are working in this field. In this paper, a review study focuses on this field is introduced to make classifications between different types of faults and diagnosis methods those used in the field of robotics. Many types of faults are studied, according to some previous and recent works. The most detected faults can be classified into two parts: hardware and software faults. The hardware faults part is further classified into two main types; the first one is represented in sensors and actuators, while the other is included taking into consideration both position and velocity in joints. These joints which usually connect the links of the arm with each other and ensure contentions to motors, controllers, and many sensors, are really represent the most important side have to be studied. The software faults part includes those errors occurred during programming such as any error happen in signal translation, signal classification or signal identification is considered as a software fault.

 In biometrics field, usually feature vectors have major length and contain ineffective information. This problem is so called “curse of dimensionality‟. Hence, there is a need for efficient dimensionality reduction technique to remove the redundant features and reduce the size of feature vectors to get high accuracy rate with fast performance. In this paper a comprehensive study of commonly used dimensionality reduction techniques: Principle Component Analysis, Linear Discremenant Analysis, and Generalized Discremenant Analysis, have been handled.  Theoretical background of these techniques is illustrated along with the methods used to calculate their projection spaces then; practical implementation is conducted to find out and adopt the best one for retina based biometric authentication system. From this extensive study, it has been concluded that PCA technique has a number of problems make it has a bad classification power. LDA technique has a number of problems make it impossible to implement in most cases of biometrics field, while GDA technique is more efficient than the PCA and LDA techniques for dimensionality reduction purpose. It has high classification power and consumes less computational time. Hence, GDA technique is adopted in the proposed authentication system.   

In this paper, a network service monitoring system was proposed by relying on the agent for several reasons, including the possibility of providing effective control over the network, preventing penetration, reducing complications, ensuring the continuity of service on the network, permitting quality of service, reducing downtime and system cost. The proposed network management and monitoring system includes a set of tasks such as (monitoring the network service using a simple interface, the ability to add and delete new users, provide security, and the ability to distribute monitoring tasks to many agents and make adjustments independently without user intervention). The proposed monitoring system can be applied to the internet or local networks. The agent monitors and observes events on the network and collects information from all parts of the network and sends it to the server to convert it to a page that is designed to display this information in real-time to the administrator. Event monitoring information on the network is collected at the user's request or on a scheduling system created by the network manager and sent this information to the server to alert the manager when a fault occurs. By providing the ability to make some decisions without consulting the manager. This system has been designed to be general in all types of networks in the sense that it can be used in monitored and manage the network activated or passive, and it can be applied in the local networks and global networks.

High Level Synthesis (HLS) tool does not only simplify the designing operation and rapid prototyping but also allows the designers to explore large number of design’s techniques such as parallelism, pipeline, memory partitioning and many other techniques. Turbo decoder based on Maximum APosterior Probability (MAP) algorithm is designed in this work using Vivado HLS. The normal turbo decoder with two MAP decoders were implemented with and without parallelism and proposed a new design of turbo decoder with one MAP decoder and it was designed with and without parallelism using different window technique in HLS tool which it is not explored previously. These designs were implemented for different frame size in this work. A comp-arison in latency and resource utilization where done and how a tradeoff done between these two parameters to reach the specific design that we need. The new design produces better results.

Advancments in technologies can help solve many problems. Internet of Things (IoT), a recent technology, can be employed to tackle the problems with irrigation systems in Iraq that suffer from agricultural pests. Such pests are known as emergence of bushes and weeds, such as (Eichhornia and Ceratophyllum), that spread in waterways, stream and river back, estuaries, irrigation channels, gates, and systems.They basically impedethe flow of water and affect the fucntion of pumps, gates and sprinklers, and can evencause them to stop working. Agricultural pests, in addition, consume huge amounts of water that Iraq critically needs, especially in the years of drought and lack of rain.The present study shows the deisgn of a system, for monitoring and controlling the agricultural pests, that uses IoT Wi-Fi Photon board with a GUI (Graphical User Interface) which is supported with an early notification system.The reasons for the growth of these pests and their spread are discussed in this study. Moreover, there are two methods suggested to limit the emergence of the Ceratophyllum plant and detect of the Eichhornia from an early stage. The results showed that the proposed system is feasible.

The research aims to design and implement a prototype for an automated system that reads electrical energy meters for the consumers and collects these readings in a central unit via the World Wide Web (the Internet). This is done by adding a camera that automatically captures the meter reading of the electric meter as an alternative to the mobile meter reader. This meter reading image is processed and the value of the meter reading is extracted by using a Raspberry Pi device and the Python language depending on OCR (Optical Character Recognition) algorithm and then sent via Internet and collected from all consumers through the Internet cloud in a database in the Central Electricity Department. After collecting this information, it can be used to monitor electrical loads, record invoices, and give reports about loads and costs to consumers, and thus participate in rationalizing electrical energy consumption.

The voxelization process is an essential stage in three dimensional (3D) graphics pipeline. Its implementation should precede displaying objects in the pipeline. In this paper, different Voxelization algorithms are modified and parallelized to accelerate the operation of this stage. The 3D Digital Differential Analyzer (DDA) algorithm is used for line voxelization. This algorithm is utilized in triangle filling using the scan-line and the edge-function algorithms. The first one is designed to produce lines in parallel while the second can produce voxels. All these algorithms are parallelized using CUDA architecture and implemented on GPU processor. The actual implementation of these algorithms is examined and optimized according to the occupancy and block size metrics. The experimental results show that the acceleration amount of 3D DDA was about 4352x max compared to the OpenGL implementation, and the edge function implementation has been executed at a higher speed than the scan-line for object triangles voxelization.

The upper limb disability experience includes both the loss of functional skills as well as a hand's sensation. Sensation ability, it’s very important to human experience and helps him to reach a good interaction with surrounding. Also, Feedback from robot arm is very important for understanding the protection for the robot arm and providing contact between human and arm. Research studies to regain sensation through many technics This paper proposed a heat sensation system, this system transfers the heat at the end of each robot arm finger to a specific position. The heating pad is used to generate similar temperature at fingers. System sensation was tested and evaluated to reach the desirable response. The results show the ability of the system to transfer temperature on a healthy position at handicapped.

Wavelet Packet Based Multicarrier Modulation (WPMCM) system uses usually a prototype filter bank multicarrier. The Daubechies-D10 filter bank (D10FB) is the basic framework of multicarrier modulation (MCM) transceiver system. In this paper, Lattice structures of exact Daubechies-D10 wavelet filter are adopted to design a prototybe filter bank realized for a proposed structure of WPMCM transceiver system. Magnitude and phase responses of the exact Daubechies-D10 LPF and the proposed structure are compared. They are nearly the same in the passband with improved roll-off characteristics of the magnitude response of the proposed. Whilefrom the results, it appears that the proposed WPMCM structure possess low speed of operation, less complexity and less power consumption.It is also noticed from SNR comparison, that the performance evaluation of the proposed WPMCM transceiver system is a moderate between other two previously issued structures.

In this paper an efficient Real-Time Voice over Wireless sensor network (VoWSN) platform based on Automatic Speech Recognition (ASR) system to be used in emergency scenarios is proposed, implemented and evaluated. The workflow principle of the proposed system is depending on a Category Transformation Protocol (CTP) that transforms system category gradually from network dependent ASR system with a full dictionary and language model (i.e. large vocabulary) to fully embedded ASR system with customized dictionary and language model (i.e. small vocabulary ). Moreover, a comparison study has been performed between our proposed VoWSN based ASR system and a VoWSN based streaming system. This comparison is performed to elaborate the gains achieved when sending the text of the voice signal instead of sending the voice signal. Additionally, the Voice over IoTs (VoIoTs) system has been evaluated utilizing Voice streaming or ASR system to evaluate the system performance when connecting to the Internet.