Energy-aware strategy for data forwarding in IoT ecosystem

The Internet of Things (IoT) is looming technology rapidly attracting many industries and drawing research attention. Although the scale of IoT-applications is very large, the capabilities of the IoT-devices are limited, especially in terms of energy. However, various research works have been done to alleviate these shortcomings, but the schemes introduced in the literature are complex and difficult to implement in practical scenarios. Therefore, considering the energy consumption of heterogeneous nodes in IoT eco-system, a simple energy-efficient routing technique is proposed. The proposed system has also employed an SDN controller that acts as a centralized manager to control and monitor network services, there by restricting the access of selfish nodes to the network. The proposed system constructs an analytical algorithm that provides reliable data transmission operations and controls energy consumption using a strategic mechanism where the path selection process is performed based on the remaining energy of adjacent nodes located in the direction of the destination node. The proposed energy-efficient data forwarding mechanism is compared with the existing AODV routing technique. The simulation result demonstrates that the protocol is superior to AODV in terms of packet delivery rate, throughput, and end-to-end delay

Hydrogeological Risk Management in Smart Cities: A New Approach to Rainfall Classification Based on LTE Cell Selection Parameters

The sudden climate change, that has taken place in recent years, has generated calamitous phenomena linked to hydrogeological instability in many areas of the world. An accurate estimate of rainfall levels is fundamental in smart city application scenarios: it becomes essential to be able to warn of the imminent occurrence of a calamitous event and reduce the risk to human beings. Unfortunately, to date, traditional techniques for rainfall level estimation present numerous critical issues. This paper proposes a new approach to rainfall classification based on the LTE radio channel parameters adopted for the cell selection mechanism. In particular, this study highlights the correlation between the set of radio channel quality monitoring parameters and the relative rainfall intensity levels. Through a pattern recognition approach based on neural networks with Multi-Layer Perceptron (MLP), the proposed algorithm identifies five classes of rainfall levels with an average accuracy of 96 % and a F1 score of 93.6 %

Updates of Wearing Devices (WDs) In Healthcare, And Disease Monitoring

 With the rising pervasiveness of growing populace, aging and chronic illnesses consistently rising medical services costs, the health care system is going through a crucial change from the conventional hospital focused system to an individual-focused system. Since the twentieth century, wearable sensors are becoming widespread in medical care and biomedical monitoring systems, engaging consistent estimation of biomarkers for checking of the diseased condition and wellbeing, clinical diagnostics and assessment in biological fluids like saliva, blood, and sweat. Recently, the improvements have been centered around electrochemical and optical biosensors, alongside advances with the non-invasive monitoring of biomarkers, bacteria and hormones, etc. Wearable devices have created with a mix of multiplexed biosensing, microfluidic testing and transport frameworks incorporated with flexible materials and body connections for additional created wear ability and effortlessness. These wearables hold guarantee and are fit for a higher understanding of the relationships between analyte focuses inside the blood or non-invasive biofluids and feedback to the patient, which is fundamentally significant in ideal finding, therapy, and control of diseases. In any case, cohort validation studies and execution assessment of wearable biosensors are expected to support their clinical acceptance. In the current review, we discussed the significance, highlights, types of wearables, difficulties and utilizations of wearable devices for biological fluids for the prevention of diseased conditions and real time monitoring of human wellbeing. In this, we sum up the different wearable devices that are developed for health care monitoring and their future potential has been discussed in detail