Physical layer security and energy efficiency over different error correcting codes in wireless sensor networks

Despite the rapid growth in the market demanding for wireless sensor networks (WSNs), they are far from being secured or efficient. WSNs are vulnerable to malicious attacks and utilize too much power. At the same time, there is a significant increment of the security threats due to the growth of the several applications that employ wireless sensor networks. Therefore, introducing physical layer security is considered to be a promising solution to mitigate the threats. This paper evaluates popular coding techniques like Reed solomon (RS) techniques and scrambled error correcting codes specifically in terms of security gap. The difference between the signal to nose ratio (SNR) of the eavesdropper and the legitimate receiver nodes is defined as the security gap. We investigate the security gap, energy efficiency, and bit error rate between RS and scrambled t-error correcting codes for wireless sensor networks. Lastly, energy efficiency in RS and Bose-Chaudhuri-Hocquenghem (BCH) is also studied. The results of the simulation emphasize that RS technique achieves similar security gap as scrambled error correcting codes. However, the analysis concludes that the computational complexities of the RS is less compared to the scrambled error correcting codes. We also found that BCH code is more energy-efficient than RS

Space-Time Frequency Block Codes in LTE-DSRC Hybrid Vehicular Networks

In vehicular communication systems, Dedicated Short Range Communication (DSRC) is said to provide fast communication and high security between vehicles. Simultaneously, Long-Term Evolution (LTE) is used due to its high bandwidth, low latency, and high spectrum efficiency. The DSRC and LTE hybrid model has gained much attention as it is feasible and simpler in design and deployment. In fact, multiple-input multiple-output (MIMO) systems have been widely used in modern wireless communication systems to enhance data throughput, reliability, and coverage. This paper proposes a MIMO LTE-DSRC hybrid system using space-time frequency block codes (STFBC). This paper focuses on the physical layer performance of the LTE-DSRC hybrid uplink structure. The DSRC Orthogonal Frequency Division Multiplexing (OFDM) transmitter and LTE Single Carrier Frequency Division Multiplexing (SCFDM) receiver are used for the uplink transmission. A study on bit error rate (BER), pairwise error probability (PEP), and channel-to-interference ratio (CIR) of the 2x2 MIMO LTE-DSRC system is conducted. The numerical results show that this proposed method improves the error rate performance with a gradual increase in signal-to-noise ratio (SNR) compared to the baseline systems

IoT-based monitoring and data-driven modelling of drip irrigation system for mustard leaf cultivation experiment

The changing dynamics, non-linearity of soil moisture content, as well as other weather and plant variables requires real-time monitoring and accurate predictive model for effective irrigation and crop management. In this paper, an improved monitoring and data-driven modelling of the dynamics of parameters affecting the irrigation of mustard leaf plant is presented. An IoT-based monitoring framework is implemented using ESPresso Lite V2.0 module interfaced with different soil moisture sensors (VH-400), flowmeter (YF-S201) as well as Davis vantage pro 2 weather station to measure soil moisture content, irrigation volume, and computation of the reference evapotranspiration (ETo). The data collected including plant images were transmitted to the Raspberry Pi 3 controller for onward online storage and the data are displayed on the IoT dashboard. The combination of both soil moisture and ETo values was used for scheduling a drip irrigated plant grown in a greenhouse for 35 days. A total number of 20, 703 experimental data samples are collected from the IoT-based platform was further used for data driven modelling through system identification in MATLAB. The result shows the development of different predictive models for soil moisture content prediction. The ARX prediction model is found to perform better than the ARMX, BJ and State space model in terms of estimated fit of 91.31%, 91.09%, 91.08%, and 90.75% respectively. Therefore, a robust monitoring framework for irrigation system has been developed, while the performance of the identified ARX model is promising to predict the volumetric soil water content

Indoor 3-D RT radio wave propagation prediction method: PL and RSSI modeling validation by measurement at 4.5 GHz

This article introduces an efficient analysis of indoor 4.5 GHz radio wave propagation by using a proposed three-dimensional (3-D) ray-tracing (RT) modeling and measurement. The attractive facilities of this frequency band have significantly increased in indoor radio wave communication systems. Radio propagation predictions by simulation method based on a site-specific model, such as RT is widely used to categorize radio wave channels. Although practical measurement provides accurate results, it still needs a considerable amount of resources. Hence, a computerized simulation tool would be a good solution to categorize the wireless channels. The simulation has been performed with an in-house developed software tool. Here, the 3-D shooting bouncing ray tracing (SBRT) and the proposed 3-D ray tracing simulation have been performed separately on a specific layout where the measurement is done. Several comparisons have been performed on the results of the measurement: the proposed method, and the existing SBRT method simulation with respect to received signal strength indication (RSSI) and path loss (PL). The comparative results demonstrate that the RSSI and the PL of proposed RT have better agreements with measurement than with those from the conventional SBRT outputs

Life Case: Inelastic Collision based Automobile Crash Detection and Alert System via 3G Network

Accident detection and alert systems that can pinpoint the whereabouts of an accident are crucial to ensure the concerned authorities are informed instantaneously about the occurrence of an accident, in order for the deployment of emergency response to save lives in the least amount of time. A 3G incorporated accident detection system, known as Life Case is designed to discover the accidents between automobiles and, send the timestamp, and the actual position of an accident, to a developed android application built using Android Studio, via a cloud database. The alert message is presented using Google Maps which helps user to save plenty of time through easy navigation feature towards the accident location. Life Case measures the acceleration of an automobile during a collision using the Theory of Inelastic Collision

Asynchronous V2V With NLOS Vehicular Sensing

In vehicular networks the basic and important operation is accurate vehicular sensing. The proven and existing techniques have their own limitations especially in NLoS scenarios like detecting Blocked vehicles at junctions or blocked by other bigger vehicles. For instance, various approaches are used for communication and reflection purpose which have low reliability, high latency and are incapable of detecting blocked vehicle (BV) without line-of-sight which is the main reason behind recent fatal accident in autonomous vehicles. This research will propose an elegant and novel method of BV sensing technology that exploits multi-path transmission from a BV to a detecting vehicle (DV). This technology will prove itself as a new venture because it enables the DV to detect multiple BV-state parameters including position, orientation of driving direction, and size. This research design will approach leverages estimated information on multi-path (namely their AoA, AoD, and ToA) and their geometric relations using the MUSIC algorithm. We will study their feasibility conditions in terms of the required number of paths. The accuracy of the proposed technique will be validated by its realistic simulation