A Survey on the Viability of Confirmed Traffic in a LoRaWAN <s> B. SMART HEALTH <s> Internet of Things (IoT) technology has attracted much attention in recent years for its potential to alleviate the strain on healthcare systems caused by an aging population and a rise in chronic illness. Standardization is a key issue limiting progress in this area, and thus this paper proposes a standard model for application in future IoT healthcare systems. This survey paper then presents the state-of-the-art research relating to each area of the model, evaluating their strengths, weaknesses, and overall suitability for a wearable IoT healthcare system. Challenges that healthcare IoT faces including security, privacy, wearability, and low-power operation are presented, and recommendations are made for future research directions. <s> BIB001 </s> A Survey on the Viability of Confirmed Traffic in a LoRaWAN <s> B. SMART HEALTH <s> The modern-day scenario of the global cold chain pharmaceutical industry has called upon the cold chain logistics as the need of the hour. The cold chain logistics industry is being crippled with challenges like increased product volume and sensitivity, ever growing regulations and infrastructural gaps in the form of location tracking issues and controlled environment monitoring all along the cold chain. These challenges call for the invasion of disruptive technologies in the logistics industry and our project aims to do the same. We aim to reduce the extent of human presence all along the cold chain by means of a powerful tool in the form of the Internet of Things (IOT). Due to the increased sensitivity of the modern-day vaccines and other pharmaceutical products, we must ensure that the vigor of the product remains intact and also ensure that any details regarding instances of equipment failure leading to product spoilage or an event of a successful delivery must be communicated back to the manufacturer's/retailer's end as soon as possible. Our project seeks to fill gaps involving location tracking and environment control by means of a GPS module and an IOT based sensor platform respectively. The sensor data is sent via Wi-Fi transmitter with receiving end involving the monitoring officer who will receive regular updates on the controlled environment parameters, the location of the transporting locomotive. The monitoring officer now has regular updates about the parameters and thus permitting the officer to take swift actions in cases of emergency scenarios as explained during the course of the project report. <s> BIB002 </s> A Survey on the Viability of Confirmed Traffic in a LoRaWAN <s> B. SMART HEALTH <s> The proliferation of embedded systems, wireless technologies, and Internet protocols have enabled the Internet of Things (IoT) to bridge the gap between the virtual and physical world through enabling the monitoring and actuation of the physical world controlled by data processing systems. Wireless technologies, despite their offered convenience, flexibility, low cost, and mobility pose unique challenges such as fading, interference, energy, and security, which must be carefully addressed when using resource-constrained IoT devices. To this end, the efforts of the research community have led to the standardization of several wireless technologies for various types of application domains depending on factors such as reliability, latency, scalability, and energy efficiency. In this paper, we first overview these standard wireless technologies, and we specifically study the MAC and physical layer technologies proposed to address the requirements and challenges of wireless communications. Furthermore, we explain the use of these standards in various application domains, such as smart homes, smart healthcare, industrial automation, and smart cities, and discuss their suitability in satisfying the requirements of these applications. In addition to proposing guidelines to weigh the pros and cons of each standard for an application at hand, we also examine what new strategies can be exploited to overcome existing challenges and support emerging IoT applications. <s> BIB003 </s> A Survey on the Viability of Confirmed Traffic in a LoRaWAN <s> B. SMART HEALTH <s> This paper presents an advanced Internet of Things point-of-care bio-fluid analyzer; a LoRa/Bluetooth-enabled electronic reader for biomedical strip-based diagnostics system for personalized monitoring. We undertake test simulations (technology trial without patient subjects) to demonstrate potential of long-range analysis, using a disposable test ‘key’ and companion Android app to form a diagnostic platform suitable for remote point-of-care screening for urinary tract infection (UTI). The 868 MHz LoRaWAN-enabled personalized monitor demonstrated sound potential with UTI test results being correctly diagnosed and transmitted to a remote secure cloud server in every case. Tests ranged over distances of 1.1–6.0 Km with radio path losses from 119–141 dB. All tests conducted were correctly and robustly received at the base station and relayed to the secure server for inspection. The UTI test strips were visually inspected for correct diagnosis based on color change and verified as 100% accurate. Results from testing across a number of regions indicate that such an Internet of Things medical solution is a robust and simple way to deliver next generation community-based smart diagnostics and disease management to best benefit patients and clinical staff alike. This significant step can be applied to any type of home or region, particularly those lacking suitable mobile signals, broadband connections, or even landlines. It brings subscription-free long-range bio-telemetry to healthcare providers and offers savings on regular clinician home visits or frequent clinic visits by the chronically ill. This paper highlights practical hurdles in establishing an Internet of Medical Things network, assisting informed deployment of similar future systems. <s> BIB004 </s> A Survey on the Viability of Confirmed Traffic in a LoRaWAN <s> B. SMART HEALTH <s> Falls in older adults are a major cause of morbidity and mortality and are a key class of preventable injuries. This paper presents a patient-specific (PS) fall prediction and detection prototype system that utilizes a single tri-axial accelerometer attached to the patient’s thigh to distinguish between activities of daily living (ADL) and fall events. The proposed system consists of two modes of operation: 1) fast mode for fall predication (FMFP) predicting a fall event (300–700 msec) before occurring and 2) slow mode for fall detection (SMFD) with a 1-sec latency for detecting a fall event. The nonlinear support vector machine classifier (NLSVM)-based FMFP algorithm extracts seven discriminating features for the pre-fall case to identify a fall risk event and alarm the patient. The proposed SMFD algorithm utilizes a Three-cascaded 1-sec sliding frames classification architecture with a linear regression-based offline training to identify a single and optimal threshold for each patient. Fall incidence will trigger an alarming notice to the concern healthcare providers via the Internet. Experiments are performed with 20 different subjects (age above 65 years) and a total number of 100 associated falls and ADL recordings indoors and outdoors. The accuracy of the proposed algorithms is furthermore validated via MobiFall Dataset. FMFP achieves sensitivity and specificity of 97.8% and 99.1%, respectively, while SMFD achieves sensitivity and specificity of 98.6% and 99.3%, respectively, for a total number of 600 measured falls and ADL cases from 77 subjects. <s> BIB005
Smart health is an area in which tremendous growth is expected to occur due to technological advancements and the rise in the global life expectancy BIB003 . This area is quite broad as it contains not only the detection of an illness but also the long term monitoring of health conditions/illnesses. Smart health applications frequently have strict QoS requirements, but this is also application-specific. Real-time systems monitoring glucose levels or heart rhythms require low communication delay, whilst other systems such as fall detection are sensitive to packet loss  , BIB003 . These systems differ as some systems simply transmit sensor data whilst others process the data and only send updates. One example of a system where the data is processed locally and only alerts are sent is fall detection BIB005 . A device is attached to a person and continually examines accelerometer data to determine when an alert to indicate a fall has occurred must be sent. Another example is the use of LoRaWAN in an IoT bio-fluid analyzer testing for urinary tract infections BIB004 . The analyzer sends the result of a test to a remote secure server, the use of acknowledgements here can ensure that the patient's test results were captured. LoRaWAN was evaluated as a potential technology for smart health in BIB001 . It was deemed to be suited in most cases due to its range, latency and network capacity capabilities. The use of Class A was deemed a good compromise between battery efficiency and receiving an acknowledgement for transmitting health data. In many cases it is not that all data be received successfully, only critical data such as an alert of a potential heart attack or fall will require acknowledgement. Another aspect of smart health is ensuring the cold chain is kept intact for products such as insulin and vaccines BIB002 . These products have strict acceptable temperatures ranges in which items must be kept during their transportation, storage and handling. If this acceptable range is breached, it is critical that any sent alerts are received, as this item should no longer be considered safe to use.