Data Reduction in Body Sensor Networks Using Wavelet Principal Components Analysis

This paper characterizes an approach to data compression and defect isolation for the multi-variable process by introducing the wavelet principal component analysis (PCA) and the genetic algorithms. In the defect analysis process, data compression is a critical phase. In our case of study, this can be achieved through the wavelet PCA. We can, through the use of such a technique, filter the data noise and the measurement errors by combining the PCA and the wavelet analysis. The genetic algorithm optimization feature is then employed in structuring the residues of the defect isolation. We present the principle of the PCA as well as the wavelet compression property. Then, we describe both the defect isolation classical method by structuring the residues and the principle of optimizing a problem by the genetic algorithms. The proposed approach is implemented on a statistic system and the Tennessee Eastman process. In comparison with other previous methods, the obtained results mirror the performance of the approach to defect isolation.

Classification of heavy metal Cd stress in lettuce leaves based on WPCA algorithm and fluorescence hyperspectral technology

The introduction of the Wireless Body Area Network (WBAN) grows significantly regarding its flexibility, accuracy, costs efficiency and mobility. It supports a huge range of innovative applications that improve the quality of life and enhance services. In the health care system, the majority of WBAN applications are responsible of handling critical data in order to monitor the patient health state and to save his live in many cases. That's why WBAN should efficiently deliver patient's vital signs to specialized medical entity (doctor, emergency, ‥). However, the particular architecture of WBAN and the movement patterns of the body part affect the communication quality. Moreover, the number of WBAN nodes increases the contention level to access to the shared wireless medium; this consequently produces packets collisions and the loss of critical data. We evaluated in this article the performance of the WBAN within different scenarios. We investigated different effects of the number of nodes as well as the different body state (standing, running) on the WBAN's reliability. We, finally, proposed a simple, no cost and convenient Adaptive Transmit Power Mechanism (ATPM) to improve the WBAN link quality without consuming unnecessary energy.

Body Area Network (BAN) is widely used in medical healthcare systems. Under WSN (Wireless Sensor Network) technology many applications are developed in Body Area Network (BAN). In medical applications the sensor network is widely used now days. Applications like Healthcare Monitoring System, Smart Hospitality, and Continuous patient monitoring system are under Body Area Network (BAN) technology. Sensors are attached on the body of patient by which values are to be taken, analyzed for healthcare system. WBAN offers wide variety for evaluation of healthcare in medical systems. Various sensors can be connected to the on clothing or on-body and also implanted under skin. There sensors are used to calculate the parameters from the body of patient. And the values are taken from sensors is given to the analyzing device or hardware by the wired or wireless devices such as Bluetooth, Zigbee etc. BAN gives wide availability of healthcare devices all the time. Projects are done in Body Area Network (BAN) from 1976. A wearable computer, sensor network based medical monitoring system, Europian Mobihealth etc. are some of the examples of project in WBAN. Wireless Body area network is now often used in Mobile Health Application and it is emerging technology which gives facilities for human health applications.

In this paper, we evaluate the performance of UMTS (Universal Mobile Telecommunication System) downlink system in vicinity of a healthcare system. We assume that the healthcare system is a body area network (BAN) system which is based on UWB (Ultra Wide Band) technology. So, the effect of UWB BAN system on UMTS system is investigated by simulation. From the simulation results, we found that the UMTS system is considerably affected by the UWB BAN interference. However, in order to battle this interference and achieve good performance for UMTS system, we found that it is very necessary to carefully raise the UMTS base station transmitted power against that of UWB BAN system. So, the minimum requirements for UMTS system to overcome this interference are stated in this work.

Body Area Network (BAN) is a network of wireless medical sensors, deployed on a person, for enabling pervasive, individualized, and real time health management. Securing inter-sensor communications within BANs is essential for preserving not only the privacy of health data but also for ensuring safety of healthcare-delivery. The proposed technique presents a scheme for enabling secure inter sensor communication within BAN. The proposed method allows neighbouring nodes in a BAN to agree to a symmetric (shared) cryptographic key, in an authenticated manner, using physiological signals obtained from the subject. The proposed method generates the key from the physiological signals sensed by the sensors and converts it into frequency domain and generates features. The generated features are transformed into a cubic spline curve and the coefficients are concatenated to form the key. The key is then transmitted to the receiver by a new fuzzy vault cryptographic method, where the receiver decrypts (using cubic spline interpolation) and finds the key. This key agreement can provide security for the e-health applications.

Wireless Body area Networks (WBANs)- groups of sensors deployed inside a human body- are envisioned to improve the healthcare domain by continuously monitoring and reporting patient's health to the health care systems. However, the nature of openly deployed sensor nodes, coupled with the lack of security, make it easy for intruders to attack WBANs. In this paper, we propose a new scheme, PMAS, to achieve mutual authentication between a cell phone (personal device representing the sink) and WBANs' sensor nodes. In addition, based on a modified idea of Diffie-Hellman key exchange scheme, we establish a shared secret key between that sink and every sensor node in the network. The security analysis shows that PMAS thwarts different attacks, including the replay, fake sink, fake sensor, and Denial of Service (DOS) attacks. Furthermore, comparing to previous authentication schemes, the computation and communication overheads added by our scheme are much smaller than those in previous schemes.

It is worth mentioning that the growing use of wireless sensor networks, evolution in Nano biosensors and micro medical equipment, remote health monitoring has affected treatment. Since people have tended to ubiquitous health monitoring, real time medical health care systems will have great significance. It is crystal clear that offering a new design of Wireless Body Area Network (WBAN) in real time healthcare's system is very important. To pave the way for the discussion, we would like to pay your attention to the previous studies in which we have improved energy efficiency and security in WBAN. To pave the way for further discussion now, we would like to review the third aspect of WBAN challenge in maximum efficiency and performance, with the approaching security and optimal energy in the real time health care system applications. In a word, in this paper urgency of using WBAN for real time telemedicine is to be discussed.

Wireless Body Area Networks (WBANs) are integral to modern healthcare systems, providing continuous health monitoring and real-time data transmission. The sensitivity of medical data being transmitted makes security a significant concern in WBANs. This study explores the application of the Elliptic Curve Cryptography (ECC)-based Diffie-Hellman Key Exchange (ECDH) algorithm to enhance security within WBANs. The study investigates the suitability of ECC for this context and evaluates the performance and security implications of implementing ECDH in WBANs. The findings reveal that ECDH provides a robust and computationally efficient solution for secure key exchange in WBANs, addressing inherent vulnerabilities. The adoption of ECC-based ECDH is poised to bolster data confidentiality and integrity in WBANs, promoting trust and widespread use of these networks in healthcare applications. This research contributes to the growing body of knowledge regarding security measures in WBANs and opens new avenues for the secure transmission of sensitive medical information.

This paper explores how the integration and performance of Wireless Body Area Networks (WBANs) contribute to sustainable healthcare practices. WBANs play a crucial role in reducing the environmental footprint of healthcare systems by providing continuous monitoring that can prevent unnecessary hospitalizations and reduce the consumption of disposable medical supplies. Additionally, the design of WBANs using environmentally friendly materials, low-power devices, and recyclable components is discussed to optimize the sustainability of healthcare practices. To enhance infrastructure, services, and quality of life, new technologies have been integrated to improve WBANs. Patients' essential health data may be continuously and instantly collected thanks to these networks, and healthcare providers can receive the data right away for quick analysis and action. WBANs have healthcare benefits, but there are also major drawbacks. Technologies that can combine low power consumption, minimal delay, and high enough data rates are needed for WBANs in order to support a variety of medical applications. The effectiveness of the LoRaWAN and IEEE 802.15.6 technologies in WBAN is assessed in this paper. With the use of seven crucial metrics which are throughput, arrival rate, delay, energy consumption, residual energy, network lifetime, and packet delivery ratio (PDR), this paper seeks to study which technology is appropriate with WBANs using NS3 as a simulation program. With network parameters, 1000 seconds, and 50 nodes, the paper evaluated the performance of each technology. The results show that IEEE 802.15.6 is superior in terms of throughput, PDR, and arrival rate whereas LoRaWAN is superior in terms of energy consumption, residual energy, network lifetime, and delay.

In the attack of the encryption algorithm ARCFOUR(RC4), new method of machine learning based on Wavelet Transform(WT) and Principal Component Analysis(PCA)is proposed. WT is used to reconstruct the new signals to extract information from the original signals effectively. Components in low and high frequency and reconstructed signals are made by WT. In order to analyze the impact of the signals on the success rate of prediction, four kinds of signals are adapted respectively for dimensionality reduction, which contains initial signals, reconstructed signals, and the signals in low and high frequency. By the classification of Support Vector Machine (SVM), the results show that the effect of the reconstructed signals is the best one. The reconstructed signals reduce the noise influence. In the range of 500 dimensions, the classification effect of the reconstructed signals is obviously better than others. As the dimension increases, the effect becomes small. The effect of signals in low frequency is more effective than that of the original in most of dimensions. The classification success rate is still high with fewer dimensions. In the four kinds of signals, the effect of the signals in high frequency is the worst. The results show that WT combined with PCA is a good method to handle with classification.

Nowadays, the design and construction of efficient internet of things (IoTs) has become a new strategies for improving living quality of all aspects. Emerging as one of the most significant extension of medical IoTs, wireless body area networks (WBANs) is capable of monitoring crucial physiological and behavioral information through wearable sensors, offering a new paradigm for the next-generation healthcare systems. As a matter of fact, due to the inherent open wireless communicating characteristics, data security and user privacy issues of WBANs have attracted attentions from both industry and academia. So far, lots of relevant researches emphasize on secure transmission and privacy protection. However, the computation and communication limitations for individual WBAN sensor have not been taken proper consideration. Moreover, the implementation of cloud computing infrastructure has provided WBANs with superior transmission and processing qualities. Emphasizing on the above issues, this paper construct a pairing-free authentication and sensor cooperation scheme in cloud-assisted WBANs, where most of the practical requirements for WBAN sensors could be satisfied. Our design guarantee the sensor anonymity in the whole transmission session. Note that our design offers pairing-free validation procedure followed with active sensor cooperation, which is suitable for massive sensor scenarios. The security analysis proves that our designed scheme is capable of achieving desired security properties and offer adequate resistances to the charted malicious attacks. Meanwhile, security comparison demonstrates that the proposed protocol is secure compared with the state-of-the-arts.

Wireless Body Sensor Network (BSN) is being developed with a continuously rising demand for personalized healthcare. Due to the importance of privacy and safety, the medical data transmitted in wireless BSN have to be strictly secured. Physiological Signals based Secret Sharing scheme (PSSS) aiming to automatically deploy identical secrets among nodes of BSN is considered as an important add-on security mechanism in BSN. By utilizing biometric characteristics of Physiological Signal, PSSS can be efficient and reliable, as well as free of third-party authentication and pre-distribution. In this paper, taking full advantage of randomness and similarity of physiological signals, an efficient fuzzy vault based scheme is proposed and demonstrated. Frequency-domain based Entity Identifier (EI) generation and Euclidean distance based Fuzzy Vault scheme are detailed. Results of simulation analysis show that the proposed scheme has potential applications in securing intra-network communications in body sensor networks.

A body area network (BAN) as one branch of Sensor Networks, is an inter-disciplinary area which holds great promises for revolutionising the current health care systems. BAN combines the real-time updating of biomedical data with the continuous and dynamic health care monitoring closely. A number of intelligence biomedical sensors can be integrated into a wireless BAN system, and the system can be used for prevention, diagnosis and timely treatment of various medical conditions. In this article, we propose a data fusion technique for a BAN based on biomedical signals. This proposed solution is of much lower complexity than conventional techniques and hence can significantly reduce the power consumption in the BAN. The technology is carried out by removing redundant and unnecessary sample information and shifting a large portion of processing and control loads to the remote control centre in an asymmetric manner. This approach not only reduces the power consumption of biosensor nodes in a BAN, but also ensures the integrity of the biomedical information. In addition, we present a self-designed distributed time–space correlation compressive sensing model and propose an efficient algorithm based on biomedical signals. Simulation results show that the proposed algorithm can not only reconstruct the original signal with high accuracy and but also achieve significant reduction in power consumption.

The wireless body area network (WBAN) is considered as one of the emerging wireless techniques in the healthcare system. Typical WBAN sensors, especially implantable sensors, have limited power capability, which restricts their wide applications in the medical environment. In addition, it is necessary for the healthcare center (HC) to broadcast significant notifications to different patient groups. Considering the above issues, in this paper, the novel practical WBAN system model with group message broadcasting is built. Subsequently, a secure and efficient group key management protocol with cooperative sensor association is proposed. In the proposed protocol, the Chinese remainder theorem (CRT) is employed for group key management between HC and the personal controller (PC), which also supports batch key updating. The proposed sensor association scheme is motivated by coded cooperative data exchange (CCDE). The formal security proofs are presented, indicating that the proposed protocol can achieve the desired security properties. Moreover, performance analysis demonstrates that the proposed protocol is efficient compared with state-of-the-art group key management protocols.