Novel Adaptive Transmission Protocol for Mobile Sensors that Improves Energy Efficiency and Removes the Limitation of State Based Adaptive Power Control Protocol (SAPC)

Abstract

Abstract:In this paper, we have presented a novel transmission protocol which is suited for battery-powered sensors that are worn by a patient when under medical treatment, and allow constant monitoring of health indices. These body-wearable sensors log data from the patient and transmit the data to a base-station or gateway, via a wireless link at specific intervals. The signal link quality varies because the distance between the patient and the gateway is not fixed. This may lead to packet drops that increase the energy consumption due to repeated retransmission. The proposed novel transmission power control protocol combines a state based adaptive power control (SAPC) algorithm and an intelligent adaptive drop-off algorithm, to track the changes in the link quality, in order to maintain an acceptable Packet success rate (PSR)(~99%). This removes the limitation of the SAPC by making the drop-off rate adaptive. Simulations were conducted to emulate a subject's movement in different physical scenarios-an indoor office environment and an outdoor running track. The simulation results were validated through experiments in which the transmitter, together with the sensor mounted on the subject, and the subject themselves were made to move freely within the communicable range. Results showed that the proposed protocol performs at par with the best performing SAPC corresponding to a fixed drop-off rate value.Keywords: adaptive transmission; energy efficiency; mobile sensors Background WorkThe emergence of Internet of Thing (IoT) has enabled technological capabilities to exchange data and to create a healthcare system that is efficient in terms of time, energy and cost [1]. In healthcare, body wearable sensors are used to continuously monitor the vital physiological parameters of patients in hospitals and the elderly at home, allowing them to enjoy independent living [2]. Hospitals use IoT to monitor the location of medical devices, personnel and patients. The healthcare professionals are then able to use data to create a system of proactive management with this network of devices. At the same time, such procedures are effective and are cost-effective ways of monitoring age-related illnesses [3]. For example, one Texas hospital reportedly cut the re-admission rate for patients with heart failures by 50% using predictive analysis of their individual healthcare records [4].There have been significant developments in building body wearable sensors that have low computational complexity, require little memory storage, and can be suitably implemented using simple hardware. For example, Shih-Hong Li et al. have designed a wearable sensor to detect real time wheezing [5]. In the field of medicine, the wheezing sound is usually considered as an indicator of the degree of airway obstruction. In [6], authors have developed a wearable instrumented vest

Improved Circuit Design of Analog Joint Source Channel Coding for Low-power and Low-complexity Wireless Sensors

“…radio power, a wake-up radio-receiver approach is proposed to save radio power [8]. A transmission adaptive powercontrol approach is proposed based on wireless link-quality measurement for wireless monitoring sensors [9]. An eventdriven approach is described to reduce the power consumption for large-scale wireless monitoring [10].…”