Multi-layer and Clustering based Security Implementation for an IoT Environment

IoT devices are having many constraints related to computation power and memory etc. Many existing cryptographic algorithms of security could not work with IoT devices because of these constraints. Since the sensors are used in large amount to collect the relevant data in an IoT environment, and different sensor devices transmit these data as useful information, the first thing needs to be secure is the identity of devices. The second most important thing is the reliable information transmission between a sensor node and a sink node. While designing the cryptographic method in the IoT environment, programmers need to keep in mind the power limitation of the constraint devices. Mutual authentication between devices and encryption-decryption of messages need some sort of secure key. In the proposed cryptographic environment, there will be a hierarchical clustering, and devices will get registered by the authentication center at the time they enter the cluster. The devices will get mutually authenticated before initiating any conversation and will have to follow the public key protocol.

Novel approach for hybrid MAC scheme for balanced energy and transmission in sensor devices

<p><span>Hybrid medium access control (MAC) scheme is one of the prominent mechanisms to offer energy efficiency in wireless sensor network where the potential features for both contention-based and schedule-based approaches are mechanized. However, the review of existing hybrid MAC scheme shows many loopholes where mainly it is observed that there is too much inclusion of time-slotting or else there is an inclusion of sophisticated mechanism not meant for offering flexibility to sensor node towards extending its services for upcoming applications of it. Therefore, this manuscript introduces a novel hybrid MAC scheme which is meant for offering cost effective and simplified scheduling operation in order to balance the performance of energy efficiency along with data aggregation performance. The simulated outcome of the study shows that proposed system offers better energy consumption, better throughput, reduced memory consumption, and faster processing in contrast to existing hybrid MAC protocols.</span></p>

Nanoporous Layers and the Peculiarities of Their Local Formation on a Silicon Wafer

This review presents the results of the local formation of nanostructured porous silicon (NPSi) on the surface of silicon wafers by anodic etching using a durite intermediate ring. The morphological and crystallographic features of NPSi structures formed on n- and p-type silicon with low and relatively high resistivity have also been investigated. The proposed scheme allows one to experiment with biological objects (for example, stem cells, neurons, and other objects) in a locally formed porous structure located in close proximity to the electronic periphery of sensor devices on a silicon wafer.

A review on thin films, conducting polymers as sensor devices

Thin film sensors are used to monitor environmental conditions by measuring the physical parameters. By using thin film technology, the sensors are capable of conducting precise measurements. Moreover, the measurements are stable and dependable. Furthermore, inexpensive sensor devices can be produced. In this paper, thin film technology for the design and fabrication of sensors that are used in various applications is reviewed. Further, the applications of thin film sensors in the fields of biomedical, energy harvesting, optical, and corrosion applications are also presented. From the review, the future research needs and future perspectives are identified and discussed.

Evaluation Method of Mesh Protocol over ESP32 and ESP8266

Internet of Things (IoT) is one of the newest matters in both industry and academia of the communication engineering world. On the other hand, wireless mesh networks, a network topology that has been debate for decades that haven’t been put into use in great scale, can make a transformation when it arises to the network in the IoT world nowadays. A Mesh IoT network is a local network architecture in which linked devices cooperate and route data using a specified protocol. Typically, IoT devices exchange sensor data by connecting to an IoT gateway. However, there are certain limitations if it involves to large number of sensors and the data that should be received is difficult to analyze. The aim of the work here is to implement a self-configuring mesh network in IoT sensor devices for better independent data collection quality. The research conducted in this paper is to build a mesh network using NodeMCU ESP 8266 and NodeMCU ESP 32 with two types of sensor, DHT 11 and DHT 22. Hence, the work here has evaluated on the delay performance metric in Line-of-Sight (LoS) and Non-Line-of-Sight (nLos) situation based on different network connectivity. The results give shorter delay time in LoS condition for all connected nodes as well as when any node fail to function in the mesh network compared to nLoS condition. The paper demonstrates that the IoT sensor devices composing the mesh network is a must to leverage the link communication performance for data collection in order to be used in IoT-based application such as fertigation system. It will certainly make a difference in the industry once being deployed on large scale in the IoT world and make the IoT more accessible to a wider audience.

A High-Performance Coniform Helmholtz Resonator-Based Triboelectric Nanogenerator for Acoustic Energy Harvesting

Harvesting acoustic energy in the environment and converting it into electricity can provide essential ideas for self-powering the widely distributed sensor devices in the age of the Internet of Things. In this study, we propose a low-cost, easily fabricated and high-performance coniform Helmholtz resonator-based Triboelectric Nanogenerator (CHR-TENG) with the purpose of acoustic energy harvesting. Output performances of the CHR-TENG with varied geometrical sizes were systematically investigated under different acoustic energy conditions. Remarkably, the CHR-TENG could achieve a 58.2% higher power density per unit of sound pressure of acoustic energy harvesting compared with the ever-reported best result. In addition, the reported CHR-TENG was demonstrated by charging a 1000 μF capacitor up to 3 V in 165 s, powering a sensor for continuous temperature and humidity monitoring and lighting up as many as five 0.5 W commercial LED bulbs for acoustic energy harvesting. With a collection features of high output performance, lightweight, wide frequency response band and environmental friendliness, the cleverly designed CHR-TENG represents a practicable acoustic energy harvesting approach for powering sensor devices in the age of the Internet of Things.

Software-Defined NB-IoT Uplink Framework—The Design, Implementation and Use Cases

In the radiocommunication area, we may observe a rapid growth of new technology, such as 5G. Moreover, all the newly introduced radio interfaces, e.g., narrowband Internet of Things (NB-IoT), are strongly dependent on the software. Hence, the radiocommunication software development and optimization, as well as the 3GPP technical specification, should be introduced at the academic level of education. In this paper, a software-defined NB-IoT uplink framework in the field of design is presented, as well as its realization and potential use cases. The framework may be used as an academic tool for developing, investigating, and optimizing the digital transmitter paths. The proposed realization is focused on the key elements in the physical layer of the NB-IoT interface used in the sensor devices. Furthermore, the paper also highlights the need of the data processing optimization to minimize the power consumption and usage of the resources of the NB-IoT node during transmitting gathered telemetric data.

Unstructured Noise Removal for Industrial Sensor Imaging Unit by Hybrid Adaptive Median Algorithm

Thermal noise is the most common type of contamination in digital image acquisition operations, and is caused by the temperature condition of the industrial sensor devices used in the process. When it comes to picture improvement, removing noise from the image is one of the most crucial steps. However, in image processing, it is more critical to retain the characteristics of the original picture while eliminating the noise. Thermal noise removal is a challenging problem in image denoising. This article provides a strategy based on a Hybrid Adaptive Median (HAM) filtering approach for removing thermal noise from the image output of an industrial sensor. The demonstration of this proposed approach's ability, is to successfully detect and reduce thermal noise. In addition, this study examines an adaptive hybrid adaptive median filtering approach that has significant computational advantages, making it highly practical. Finally, this research report on experiments shows the high-quality industrial sensor imaging systems that have been successfully implemented in the real world.