Intense green luminescence in Mn-doped gallogermanate nanostructured glass

Mn activated optical materials have been demonstrated to be promising for various applications such as light-emitting device, tunable lasers and smart sensors. Most of the candidates belong to the single crystals and crystalline powders and few reports involve about the glass-derived materials. In this letter, we report the fabrication of active Mn-doped nanostructured glass sample via control of the crystallization of a typical gallogermanate glass. LiGa5O8 and LiGaGeO4 can precipitate after heat-treatment and Mn centers selectively incorporate into the crystalline phase. Importantly, the luminescence can be switched from red to green color and the intensity can be simultaneously enhanced. Furthermore, the luminescence properties can be tuned via control of the phase of the nanostructured glass. The approach should be general to various transition metal dopant, thus may potentially pave an effective way for functionalization of glass and expand the category of the active optical materials.

Lightweight Payload Encryption-Based Authentication Scheme for Advanced Metering Infrastructure Sensor Networks

The Internet of Things (IoT) connects billions of sensors to share and collect data at any time and place. The Advanced Metering Infrastructure (AMI) is one of the most important IoT applications. IoT supports AMI to collect data from smart sensors, analyse and measure abnormalities in the energy consumption pattern of sensors. However, two-way communication in distributed sensors is sensitive and tends towards security and privacy issues. Before deploying distributed sensors, data confidentiality and privacy and message authentication for sensor devices and control messages are the major security requirements. Several authentications and encryption protocols have been developed to provide confidentiality and integrity. However, many sensors in distributed systems, resource constraint smart sensors, and adaptability of IoT communication protocols in sensors necessitate designing an efficient and lightweight security authentication scheme. This paper proposes a Payload Encryption-based Optimisation Scheme for lightweight authentication (PEOS) on distributed sensors. The PEOS integrates and optimises important features of Datagram Transport Layer Security (DTLS) in Constrained Application Protocol (CoAP) architecture instead of implementing the DTLS in a separate channel. The proposed work designs a payload encryption scheme and an Optimised Advanced Encryption Standard (OP-AES). The PEOS modifies the DTLS handshaking and retransmission processes in PEOS using payload encryption and NACK messages, respectively. It also removes the duplicate features of the protocol version and sequence number without impacting the performance of CoAP. Moreover, the PEOS attempts to improve the CoAP over distributed sensors in the aspect of optimised AES operations, such as parallel execution of S-boxes in SubBytes and delayed Mixcolumns. The efficiency of PEOS authentication is evaluated on Conitki OS using the Cooja simulator for lightweight security and authentication. The proposed scheme attains better throughput while minimising the message size overhead by 9% and 23% than the existing payload-based mutual authentication PbMA and basic DTLS/CoAP scheme in random network topologies with less than 50 nodes.

Motion Capture Based on Intelligent Sensor in Snow and Ice Sports

With the development of motion capture technology, it has become a reality to efficiently and quickly obtain realistic human motion information. Motion capture technology has been successfully applied in many fields such as sports competitions, animation games, and film and television production. This article is aimed at studying the application of motion capture technology based on smart sensors in ice and snow sports. Put forward the idea of applying smart sensor-based motion capture technology to ice and snow sports. This article introduces in detail smart sensors, motion capture technology, and related content of ice and snow sports and conducts specific experiments on the application of smart sensor-based motion capture technology in ice and snow sports. The experimental results show that motion capture based on smart sensor technology can help athletes improve their skills and tactics. At the same time, motion capture technology based on smart sensors is also loved by most coaches and athletes, and everyone’s satisfaction with this technology has reached more than 70%.

Aligning Patient’s Ideas of a Good Life with Medically Indicated Therapies in Geriatric Rehabilitation Using Smart Sensors

New technologies such as smart sensors improve rehabilitation processes and thereby increase older adults’ capabilities to participate in social life, leading to direct physical and mental health benefits. Wearable smart sensors for home use have the additional advantage of monitoring day-to-day activities and thereby identifying rehabilitation progress and needs. However, identifying and selecting rehabilitation priorities is ethically challenging because physicians, therapists, and caregivers may impose their own personal values leading to paternalism. Therefore, we develop a discussion template consisting of a series of adaptable questions for the patient–physician encounter based on the capability approach. The goal is to improve geriatric rehabilitation and thereby increase participation in social life and well-being. To achieve this goal, we first analyzed what is considered important for participation on basis of the capability approach, human rights, and ethics of care. Second, we conducted an ethical analysis of each of the four identified dimensions of participation: political, economic, socio-cultural, and care. To improve compliance with rehabilitation measures, health professionals must align rehabilitation measures in an open dialogue with the patient’s aspiration for participation in each dimension. A discussion template based on the capability approach allows for a proactive approach in patient information and stimulates a critical assessment of treatment alternatives while reducing the risk of imposing personal values.

Challenges Facing the Application of IoT in Medicine and Healthcare

Among all the functions of the Internet of Things, healthcare applications are the most important. The internet of Things has played a vital role in the sharing of various medical resources making it an essential factor in the field of medicine. Without the applications, it may become challenging for the medical practice to achieve some objectives. Today, information is shared freely across different networks, making it easy for practitioners and institutions to work with the available resources and deliver on the medical needs of the society. IoT has made it possible to offer smart and effective healthcare services to people. The application of smart sensors is one of the factors that has contributed to effective management of healthcare needs in the society. Wearable devices can be used to track different issues within the body. Some can be embedded to monitor different functions of the body to ensure there is effectiveness in the way medical services are delivered to such patients. The information collected in such manner, can be analyzed, aggregated and mined to do the early prediction of diseases. Processing algorithms play a vital role in helping practitioners in developing personalized treatment, which makes healthcare more economical. Apart from analyzing the effectiveness of IoT in healthcare, challenges will be discussed in this study and how they impact medicine.

Essential Oil Steam Distillation: Manufacturing 4.0

Smart sensors, self-configuration, operational flexibility, and automatic learning, among others, are technological attributes from industry 4.0 appliable to the essential oil extraction by the steam distillation process. These operations are recognized by their simplicity. Nevertheless, lack of automatic controls, process monitoring, and self-adjustment lead to uncontrolled extraction, poor yields, low quality of products. It occurs because of overexposure to high temperatures and overspending resources like energy and water. As far as capacity utilization is concerned, the optimized process is key to planning and managing the production activities.

Image Speckle Denoising for Securing Internet of Smart Sensors

How to improve utility performance when securing sensitive data is an important research problem in Internet of smart sensors. In this paper, we study secured image speckle denoising for networked synthetic aperture radar (SAR). Speckle noise of SAR affects image quality and has a great influence on target detection and recognition. MSTAR dataset is often used in image target recognition. In this paper, a subregion-based method is proposed in order to improve the accuracy of target recognition and better retain target information while filtering and denoising the image. The new method applies advanced encryption techniques to protect sensitive data against malicious attack. Firstly, the image is divided into marked areas and unmarked areas through edge extraction and hole filling. Secondly, we use different size windows and filtering methods to filter the image in different areas. The experimental results show that the proposed algorithm has obvious advantages over MR-NLM, SSIM-NLM, Frost, and BM3D filtering in terms of equivalent view number and preserving edge and structure.