Packet Delivery Research Articles

Optimizing IoT Data Aggregation: Hybrid Firefly-Artificial Bee Colony Algorithm for Enhanced Efficiency in Agriculture

The data aggregation process in this study has been enhanced by the hybrid firefly-artificial bee colony algorithm (HFABC) by increasing the average packet delivery ratio, end-to-end delay, and lifespan computation. In this study, HFABC and Multi Hop LEACH are two algorithms that are used to aggregate IoT data. Their performance is compared using evaluation criteria including average End-to-End Delay, PDR, and network lifetime. The HFABC method reduces average End-to-End Delay more effectively than Multi Hop LEACH, with gains of 2.20 to 8.66 %. This demonstrates how well it works to reduce the lag times for data transfer in IoT networks. With improvements ranging from 3.45% to 45.39%, HFABC has a greater success rate than Multi Hop LEACH in effectively delivering packets. HFABC increases network lifetime by 0.047 to 2.286 percent, indicating that it helps keep IoT networks operating for longer. For effective data aggregation in IoT networks, HFABC is a superior solution that decreases delays, improves packet delivery, and lengthens network lifetime.

Evaluation of Smart Home Platform Based on Blockchain

A smart home consists of various sensors and actuators that can communicate with each other. In addition, various home appliances have similar capabilities. Therefore, the smart home became one of the applications of the Internet of Things (IoT). In this application, arise the challenges caused by the integration of various devices that came from various vendors have a different data format and keeps the data's security. Blockchain has been proposed as one solution to address these challenges. In this paper, we investigate and evaluate the performance of the blockchain-based solution for smart home IoT. Our experiment results show that the Blockchain can secure the IoT-based smart home, but it took47% longer for packet delivery.

AODV, DSDV, and DSR Protocols of Routing: A Comparative Study in VANETs Using Network Simulator-2

Mobile Ad-Hoc Networks (MANETs) are a group or a collection of wireless moving nodes (mobile-nodes) that spontaneously forms a network and functions with-out a central controller or coordinator. Mobile Ad Hoc Networks include the subset known as Vehicle Ad Hoc Networks (VANETs). The unpredictability of the multi-hop network design is further compounded by the fact that in MANET and VANET, nodes move around at their whim. Many well-known routing methods have been proposed to facilitate data flow between the different nodes of a wireless network. The NS-2 simulation in this research paper compares the performance of the protocols (reactive and proactive) of AODV, DSR, and DSDV across a variety of metrics, including "throughput, control overhead, packet delivery ratio, and average end-to-end latency". Simulations showed that different routing protocols may optimize the (VANET) connectivity and throughout. Moreover, the evaluations also illustrates the impact of sizes for the network and routing protocols on "packet loss, packet delivery ratio, average end-to-end delay and overhead transmission".

Trust based Routing – A Novel Approach for Data Security in WSN based Data Critical Applications

Wireless technology has changed the way entities communicate with one another. Wireless networks have created several opportunities in fields such as military, health care, and habitat monitoring, to name a few. However, only a few data-critical applications are built on wireless sensor networks, such as border reconnaissance, detecting infringement, and patient monitoring. These applications require the processing of a large amount of private data. Because most applications are data-sensitive, securing data transmission among wireless sensor networks is crucial. While incorporating data security, the most important requirement of wireless sensor nodes being energy optimized also need to be kept in consideration. There are various forms of assaults that are relevant in Wireless Sensor Networks (WSN). Attacks like Black Hole attacks, sink hole attacks, False data Injection attacks etc. are the most commonly seen attacks on WSNs. The common element in all these attacks is the concept of malicious / compromised node - a node which either drops / modifies the data content while forwarding it. Existing techniques for data security generally use cryptographic algorithms, but the use of cryptographic algorithms is in contrast with the energy optimization requirement of sensor nodes. An energy efficient data security scheme needs to be developed. The proposed system analyses several attacks and proposes a multi-layer data security approach to prevent change of data / dropping of data by the compromised nodes. The proposed system is a routing protocol referred as Trust Based Routing (TBR). A concept of trust value of a node is the core idea of TBR. Forwarding node is selected based on highest trust value and thus avoid malicious / compromised nodes from being involved in the routing process. The trust factor is calculated by considering the number of packets dropped, packets rejected, and the node's remaining energy. The idea of TBR is enhanced by incorporating the concept of past trust and trust of node towards a specific destination. This proposed scheme is referred as Extended Trust Based Routing (ETBR). This scheme is further enhanced by including Direct Trust, Indirect Trust and Energy Trust concepts. This scheme is referred as Consolidated Trust Estimation – Trust Based Routing (CTE-TBR). Network Simulator NS2 is used to simulate the proposed schemes. Various network factors are compared to classic Adhoc On-Demand Vector (AODV) and newly proposed schemes. The result indicates the effectiveness of the proposed data security scheme in terms of energy efficiency and Packet Delivery ratio (PDR).

A Novel Optimized Link-State Routing Scheme with Greedy and Perimeter Forwarding Capability in Flying Ad Hoc Networks

A flying ad hoc network (FANET) is formed from a swarm of drones also known as unmanned aerial vehicles (UAVs) and is currently a popular research subject because of its ability to carry out complicated missions. However, the specific features of UAVs such as mobility, restricted energy, and dynamic topology have led to vital challenges for making reliable communications between drones, especially when designing routing methods. In this paper, a novel optimized link-state routing scheme with a greedy and perimeter forwarding capability called OLSR+GPSR is proposed in flying ad hoc networks. In OLSR+GPSR, optimized link-state routing (OLSR) and greedy perimeter stateless routing (GPSR) are merged together. The proposed method employs a fuzzy system to regulate the broadcast period of hello messages based on two inputs, namely the velocity of UAVs and position prediction error so that high-speed UAVs have a shorter hello broadcast period than low-speed UAVs. In OLSR+GPSR, unlike OLSR, MPR nodes are determined based on several metrics, especially neighbor degree, node stability (based on velocity, direction, and distance), the occupied buffer capacity, and residual energy. In the last step, the proposed method deletes two phases in OLSR, i.e., the TC message dissemination and the calculation of all routing paths to reduce routing overhead. Finally, OLSR+GPSR is run on an NS3 simulator, and its performance is evaluated in terms of delay, packet delivery ratio, throughput, and overhead in comparison with Gangopadhyay et al., P-OLSR, and OLSR-ETX. This evaluation shows the superiority of OLSR+GPSR.

Novel Hybrid Deep Optimized Machine Learning Model for Energy Efficient Cluster Selection in Unmanned Aerial Vehicle Networks

Unmanned Aerial Vehicles (UAVs) have grown into a more powerful type of data transmission due to this rapid progress of evolution of wireless communication technology. In addition, UAVs have been proven to be effective in a variety of applications, including intelligent transport, disaster risk management, surveillance, and environmental monitoring. When UAVs are deployed randomly, however, they can effectively accomplish challenging tasks because of the UAVs’ has low battery capacity, quick mobility, and dynamic in nature orientation. Due to this reason, a new technique must be designed for an optimal energy efficient UAV clustering as well as data routing protocols. In this work proposes a new hybrid model of Emperor penguin-based Generalized Approximate Reasoning Based Intelligent Control (EP-GARIC) cluster-based network topology. Furthermore, the optimal routing function is achieved by the proposed Artificial Jellyfish Optimization (AJO). The implementation of this research is carried out using Network Simulator (NS2). The simulation results displays the effective performance of the suggested approach in terms of reduced energy consumption, improved packet delivery ratio, reduced loss, and so on over compared to the conventional approaches

Velocity Based Performance Analysis of GreedLea Routing Protocol in Internet of Vehicle (IoV)

Intelligent routing protocols for IoV have also been made possible by the convergence of IoT and machine learning algorithm. In order to make informed routing decisions, these intelligent routing protocols examine data gathered from IoT devices like vehicle sensors and traffic monitoring systems using machine learning algorithms. Moreover, as the number of vehicles increases and road networks become more complex, traditional routing protocols for ad hoc networks are being replaced by more advanced and efficient protocols. The purpose of this study is to concentrate on these unique qualities of IoVs network scenario. A combined routing method has been developed to construct periodic connectivity and find routes on-demand in order to save route data as graphs. The simulation's findings show that GreedLea routing protocol outperforms GPSR and AODV routing protocols in terms of delay and packet delivery ratio (PDR). The results demonstrate that the average AODV latency is significantly higher when there are fewer vehicles on the network. This is due to the fact that connections are frequently lost at higher speeds and lower densities, and re-establishing new channels takes a lot of time. As the number of vehicles rises, efficiency improves and the wait gets shorter. The average latency, yet, keeps increasing as vehicle density increases due to the additional overheads related with routing.

DynAuthRoute: Dynamic Security for Wireless Sensor Networks

Objectives: The research aims to design an architecture for secure transmission of data in wireless sensor networks. Methods: The method involves three main pillars: authentication, data encryption, and dynamic routing. Extensive simulations have been conducted to evaluate the suggested method in terms of energy consumption, memory footprint, packet delivery ratio, end-to-end latency, execution time, encryption time, and decryption time. Findings: For authentication, a dynamic key is used to power an improved salt password hashing method. Data encryption is performed using format-preserving encryption (FPE) with the appended salt key. Dynamic routing is implemented using a cluster-based routing technique to enhance network efficiency in terms of power consumption and security. The execution time for MD5 ranges from 15 to 22 milliseconds, while for SHA-1 it ranges from 16 to 23 milliseconds and for the proposed salt key generation it is 1 to 5 milliseconds. Similarly, in terms of energy consumption, memory footprint, packet delivery ratio, end-to-end latency, execution time, encryption time, and decryption time the proposed method shows promising results in ensuring the integrity and security of transmitted encrypted data. Novelty: The presents a novel architecture with enhanced cluster head-based selection algorithm that combines dynamic key-based authentication and secure data routing to establish a safe environment for data transmission in wireless sensor networks. This research works offers a method for encrypting text with a dynamic salt key that is safe, energy-efficient, and lightweight. Keywords: Wireless Sensor Network, Dynamic Key, Authentication, Hash function, Salt algorithm, Dynamic routing, Node clustering, Format-preserving encryption

Ocean-Current-Motion-Model-Based Routing Protocol for Void-Avoided UASNs

An increasing number of scholars are researching underwater acoustic sensor networks (UASNs), including the physical layer, the protocols of the routing layer, the MAC layer, and the cross-layer. In UASNs, the ultimate goal is to transmit data from the seabed to the surface, and a well-performed routing protocol can effectively achieve this goal. However, the nodes in the network are prone to drift, and the topology is easily changed because of the movement caused by ocean currents, resulting in a routing void. The data cannot be effectively aggregated to the sink terminal on the surface. Thus, it is extremely important to determine how to find an alternative node as a relay node after node drift and how to rebuild a reliable transmission path. Although many relay routing protocols have been proposed to avoid routing voids, few of them consider the relay node selection between the outage probability and the ocean current model. Therefore, we propose an ocean current motion model based routing (OCMR) protocol to avoid the routing void in UASNs. We predicted underwater node movement based on the ocean current motion model and designed a protection radius to construct a limited search coverage based on the optimal outage probability; then, the node with the best fitness value within the protection radius was selected as the alternative relay node using an improved WOA. In OCMR, the problem of the routing void caused by ocean current motion is effectively suppressed. The simulation results show that, compared with VBF, HH-VBF, and QELAR, the proposed OCMR platform performs well in terms of the PDR (packet delivery ratio), average end-to-end delay, and average energy consumption.

Optimizing Hybrid V2X Communication: An Intelligent Technology Selection Algorithm Using 5G, C-V2X PC5 and DSRC

Cooperative communications advancements in Vehicular-to-Everything (V2X) are bolstering the autonomous driving paradigm. V2X nodes are connected through communication technology, such as a short-range communication mode (Dedicated Short Range Communication (DSRC) and Cellular-V2X) or a long-range communication mode (Uu). Conventional vehicular networks employ static wireless vehicular communication technology without considering the traffic load on any individual V2X communication technology and the traffic dynamics in the vicinity of the V2X node, and are hence inefficient. In this study, we investigate hybrid V2X communication and propose an autonomous and intelligent technology selection algorithm using a decision tree. The algorithm uses the information from the received Cooperative Intelligent Transport Systems (C-ITS) Cooperative Awareness Messages (CAMs) to collect statistics such as inter vehicular distance, one-way end-to-end latency and CAM density. These statistics are then used as input for the decision tree for selecting the appropriate technology (DSRC, C-V2X PC5 or 5G) for the subsequent scheduled C-ITS message transmission. The assessment of the intelligent hybrid V2X algorithm’s performance in our V2X test setup demonstrates enhancements in one-way end-to-end latency, reliability, and packet delivery rate when contrasted with the conventional utilization of static technology.

Path Planning for UAVs Under GPS Permanent Faults

Unmanned aerial vehicles (UAVs) have various applications in different settings, including e.g., surveillance, packet delivery, emergency response, data collection in the Internet of Things (IoT), and connectivity in cellular networks. However, this technology comes with many risks and challenges such as vulnerabilities to malicious cyber-physical attacks. This paper studies the problem of path planning for UAVs under GPS sensor permanent faults in a cyber-physical system (CPS) perspective. Based on studying and analyzing the CPS architecture of the UAV, the cyber “attacks and threats” are differentiated from attacks on sensors and communication components. An efficient way to address this problem is to introduce a novel approach for UAV’s path planning resilience to GPS permanent faults artificial potential field algorithm (RCA-APF). The proposed algorithm completes the three stages in a coordinated manner. In the first stage, the permanent faults on the GPS sensor of the UAV are detected, and the UAV starts to divert from its initial path planning. In the second stage, we estimated the location of the UAV under GPS permanent fault using Received Signal Strength (RSS) trilateration localization approach. In the final stage of the algorithm, we implemented the path planning of the UAV using an open-source UAV simulator. Experimental and simulation results demonstrate the performance of the algorithm and its effectiveness, resulting in efficient path planning for the UAV.

MVR Delay: A Queueing Based Routing Model for C-V2X Mode 4 in VANET’s

During the last few years, the demand for vehicular ad-hoc networks (VANET) has gained great attraction in the intelligent transport system. The VANET architecture includes several critical features, such as distributed networking and the rapidly changing network topology. Due to the significant characteristics of road safety, it has gained a great deal of interest in industry and academia to enhance the safety of the road transport system. Efficient message exchange between vehicles and roadside units is a tedious task in VANET. Several techniques have been introduced to improve communication, but efficient packet delivery and delay reduction are challenging issues. Currently, the VANET technique has evolved as a “vehicle-to-everything (V2X)” communication standard. In addition, the 3GPP standards have introduced a new communication standard as an alternative to the IEEE 802.11p system. In this new release of 3GPP, two new communication modes are introduced, mode 3 and mode 4. Mode 3 requires a cellular infrastructure, whereas mode 4 can operate without cellular coverage. In this work, we focus on C-V2X mode 4 communications and present a novel routing scheme to deal with hidden terminal problems. The proposed approach generates a virtual queueing model in which efficient channel selection is performed so that packet collision and interference can be reduced by maximizing the distance in the virtual queue model. The experimental results demonstrate that the average performance of the proposed approach is obtained as 0.9383, 0.09 s, and 0.0617 in terms of packet delivery, end-to-end delay, and packet drop rate, respectively.

Detection and prevention of sinkhole attacks in MANETS based routing protocol using hybrid AdaBoost-Random forest algorithm

WSN (Wireless Sensor Network) is considered as one of the promising technologies which are utilized in various fields for various applications. Along with it, MANET (Mobile Ad Hoc Network) has attracted a distinct attention, as they serve communication means across innumerable domain. In recent years, due to the development of both wired and wireless technologies, attacks are becoming more frequent and these attacks can be in various form such as worm hole, black hole, grey-hole, sinkhole and others. These attacks can cause loss of security, increase the number of drop packets, decrease packet delivery ratio which result in poor routing performance. In order to overcome these issues, the proposed study employs PBCS (Particle Bee Colony Swarm) algorithm for finding the shortest path between the nodes, which helps in reducing the routing cost and makes the model more efficient and effective. In addition to this, Hybrid AdaBoost-Random forest algorithm is utilized in proposed model. This model helps in reducing the training time which makes the model more reliable and efficient than existing models. It can be implemented in huge dataset and in Hybrid AdaBoost-Random Forest algorithm, estimator of random forest is used, which result in high accuracy and low loss. AODV (Ad-Hoc on Demand Vector) protocol helps to identify the prevention of attack as this routing protocol perform better for longer and extensive duration of traffic than other protocols. The performance of the proposed model is evaluated using different metrics which includes accuracy, recall, precision, sensitivity and specificity. Besides, energy consumption, throughput, network lifetime, delay of the proposed model is also evaluated. The proposed model is then compared with various existing models in order to determine the efficiency and effectiveness of the proposed framework.

Multiobjective, trust‐aware, artificial hummingbird algorithm‐based secure clustering and routing with mobile sink for wireless sensor networks

AbstractWireless sensor networks (WSNs) are composed of numerous nodes distributed in geographical regions. Security and energy efficiency are challenging tasks due to an open environment and a restricted battery source. The multiobjective trust‐aware artificial hummingbird algorithm (M‐TAAHA) is proposed to achieve secure and reliable transmission over a WSN with a mobile sink (MS). The M‐TAAHA selects secure cluster head (SCH) nodes based on trust, energy, interspace between sensors, interspace between SCH and MS, and the CH balancing factor. A secure route is found by M‐TAAHA with trust, energy, and interspace between SCH and MS. The M‐TAAHA avoids the malicious nodes to improve data delivery and avoid unwanted energy consumption. The M‐TAAHA is analyzed using energy consumption, alive nodes, life expectancy, delay, data packets received in MS, throughput, packet delivery ratio, and packet loss ratio. Existing techniques (LEACH‐TM, EATMR, FAL, Taylor‐spotted hyena optimization [Taylor‐SHO], TBEBR, and TEDG) are used for comparison with the M‐TAAHA. Findings show that the energy consumption of the proposed M‐TAAHA for 1000 rounds is 0.56 J (1.78 × smaller than that of the Taylor‐SHO).

Improving Data Delivery in Unreliable Networks Using Network Coding and Ant-Colony Optimization

Wireless Sensor Networks (WSNs) comprise interconnected wireless nodes that receive and transmit data across applications and platforms. This paper addressed the problem of link failures in WSNs that potentially could lead to the loss of data packets while still in transit. This was achieved through the use of network coding which is known to address capacity bottleneck problems in WSNs. In particular, a technique called Ant Agent-Assisted Network Coding (AAANC) is proposed that employs the ant colony optimization technique in addition to network coding operations. The main aim of AAANC is to facilitate the successful delivery and decoding of coded data packets in the presence of link failures. AAANC employs a packet route selection technique that is inspired by the social behavior of natural ants. For natural ants, a strong pheromone trail along a path indicates a promising route to a food source, and this is analogous to a reliable communication link for routing data packets in this paper. Through simulations, AAANC was compared to diagonal pseudorandom network coding (DNC) and triangular pseudorandom network coding (TNC), and it proved to have a superior performance in terms of packet delivery ratio and number of decoded packets. Significant performance gain can be achieved if AAANC algorithm is made to dynamically adapt the ant colony and network coding parameters in response to traffic changes.

Relay node selection scheme and deep sleep period for power management in energy‐harvesting wireless sensor networks

SummaryThis paper presents Relay node selection scheme and Deep sleep period for power management in Energy Harvesting Wireless Sensor Networks (RD‐EHWSN), a new energy‐saving scheme founded on asynchronous duty cycling. RD‐EHWSN reduces sensor node energy consumption and guarantees equilibrium energy use between sensor nodes in WSN with the energy harvesting capacity by adjusting these sensor nodes duty cycles more drastically and deeply by according to the estimated value of its residual energy on the basis of future‐presented harvested energy, and this is done through the use of a new proposed energy threshold policy. RD‐EHWSN also grips the benefit of transmitter initiated using the low power listening (LPL) technique with short preamble messages and uses a new relay node selection procedure to achieve the load balancing in WSN. We implemented RD‐EHWSN by using OMNeT++/MiXiM. For evaluation, we compared it with PS‐EHWSN, under multiple concurrent multihop traffic flows scenarios and scenarios in which nodes can harvest different energy harvesting rate. In all experiments, RD‐EHWSN significantly outperformed the PS‐EHWSN scheme; the results of simulation demonstrate that our scheme enhances the general yielding of WSN thru lessening the energy consumption and the mean latency, as well as raising the packet delivery ratio and the throughput. Moreover, RD‐EHWSN improves the WSN lifetime and ensures it operates in good condition in the case where the energy harvesting rate is lower by comparing it with the PS‐EHWSN scheme.

CC2530-Based Wireless Data Long-Distance Communication Simulation Design and Application

With the rapid development of IoT, low-power wireless networks are becoming more and more important in engineering applications. For different IoT applications, a variety of corresponding low-power wireless technologies are studied and used. Among them, ZigBee technology is widely used for wireless data long-distance communication networks that require low-power consumption, low communication rate and large capacity self-organizing networks. However, the standard ZigBee module is limited by the large noise factor of the receiver and the small radiation power of the transmitter in the module, which cannot meet the requirements of long-distance communication. In this paper, we combine RF and communication technologies to design a long-range, low-power transceiver based on ZigBee technology for wireless data long-range communication simulation design and application. Experimental results show that the model in the urban area of 500[Formula: see text]m range, the system’s packet loss rate is kept at a low 0.03 or so, and the average Rssi is kept above and below [Formula: see text][Formula: see text]dBm, which can meet the general communication requirements and achieve the expected communication effect. Under the same packet rate, the model combines the improved AODVjr and Cluster_Tree algorithms, and the packet delivery rate can reach 98.5%, which greatly extends the wireless data long-distance communication life.

Integrating Intelligent Systems in MANET- IoT Environment based on Subjective Context

The Internet of Things (IoT) has cultivated a promising environment, pivotal across diverse sectorsvia MANET protocols within the w.w.w. This technology significantly contributes to advanced services for mobiledevices in the MANET-IoT domain. However, MANET encounters security challenges, notably malicious attacksas a prime concern. To counter these threats, preventive measures like subjective-context evaluation and nodeprotection are employed, ensuring data packet integrity before delivery. This study aims to enhance theperformance of a novel reactive protocol, integrated with a fuzzy system within the MANET-IoT environment. Themethodology is implemented in two directions: 1) Establishing a secure network founded on trust parameters andshortest path selection. 2) Incorporating an integrated fuzzy system into an improved reactive routing protocolwithin the MANET environment. Subjective context ensures a secure milieu, evaluating nodes before packetdelivery based on trust and shortest path. The fuzzy system's rules determine the network's probability distribution,contingent upon trust and the number of hop counts. The proposed routing protocol is evaluated both pre- and postattacks during packet transmission. Results demonstrate its superiority in packet transmission over the originalprotocol. Three scenarios evaluate packet delivery fraction (PDF), end-to-end delay (E2E), and normalized routingload (NRL). FS-AODV's percentages were 0.9873% against AODV's 1.9871% without drop) and 0.8419% with adrop for PDF. FS-AODV's percentages stood at 0.0006% against AODV's 0.0007% without a drop and 0.0005%with a drop for E2E. In contrast, FS-AODV's percentage was 0.058%, AODV at 0.0127% without a drop, and0.066% with a drop for NRL.

Enhancing Network Security through Advanced Authentication and Key Management Mechanisms

This paper introduces the SEAKS-PKMv2 protocol, a robust security mechanism aimed at addressing vulnerabilities within the PKMv2 framework, particularly focusing on mutual authentication, key management, and encryption in mobile WiMAX networks. By integrating RSA-based and EAP-based authentication methods, SEAKS-PKMv2 establishes a secure environment that mitigates risks such as replay, man-in-the-middle and interleaving attacks. The protocol adopts a distributed authentication and localized key management approach, facilitating efficient and secure network access and data transmission. Through simulation, we evaluate the SEAKS-PKMv2 protocol’s performance in terms of packet delivery ratio, overhead, processing time, and resilience against rogue relay station attacks. The findings demonstrate significant improvements in network security and efficiency, confirming the effectiveness of SEAKS-PKMv2 in enhancing the integrity and confidentiality of communications in distributed network settings.

Privacy-Preserving Wireless Sensor Networks for E-Healthcare Applications

Wireless sensor networks (WSNs) are a powerful support system for the fundamental infrastructure that is required to monitor physiological and activity parameters (WSN). Wearable devices, which are also referred to as wireless nodes in the scientific world, are what are used in order to measure one or more of the user’s vital signs. Each and every wireless node is a teeny-tiny device that is meant to be supplied with enough amounts of storage space, power, and transmission capability. The loss of data packets may occur during the transmission of data via a wireless medium for a number of reasons. These reasons include interferences, improper deployment circumstances, distance, and inadequate signal strength. The monitoring of a user’s physiological information and postural activity information in various applications, such as home care and hospital care, is the primary emphasis of this study. In this work, the WSN was shown thanks to the introduction of wireless sensor nodes that were created locally. These wireless sensor nodes are used in the process of analyzing many aspects of a network, such as the received signal strength, transmission offset, packet delivery ratio (PDR), and signal-to-noise interference. The work significantly improves the capabilities of conventional WSN by implementing a variety of alternative communication approaches, such as network-coded cooperative communication (NC-CC) and cooperative communication (CC). The system that is being shown makes it feasible to localize the user’s approximate position inside an indoor setting without making use of any camera network connections. This is made possible by the system’s ability to determine the user’s location via triangulation. This is one of the benefits that the system provides. A hospital sensor network, an example of which is being shown here, is capable of doing real-time monitoring of a patient’s postural activity as well as their general health. The method is being promoted in order to ensure that the patient will get assistance in a timely manner that is adequate to his/her needs. Involving NC-CC enables the effective sharing of real-time data among the group of privileged duty nurses while simultaneously minimizing the amount of network traffic, latency, and throughput. This is possible because of NC-CC protocol. The findings of the experiments showed that the proposed method of communication, which is known as dynamic retransmit/rebroadcast decision control, is a significant advancement in the network coding approach that is presently being utilized. This was demonstrated by the fact that the method was shown to be significantly more effective.