Steps to build a DIY low-cost fixed-wing drone for biodiversity conservation.

Despite the proved usefulness of drones in biodiversity studies, acquisition costs and difficulties in operating, maintaining and repairing these systems constrain their integration in conservation projects, particularly for low-income countries. Here we present the steps necessary to build a low-cost fixed-wing drone for environmental applications in large areas, along with instructions to increase the reliability of the system and testing its performance. Inspired by DIY (Do It Yourself) and open source models, this work prioritizes simplicity and accounts for cost-benefit for the researcher. The DIY fixed-wing drone developed has electric propulsion, can perform pre-programmed flight, can carry up to 500 g payload capacity with 65 minutes flight duration and flies at a maximum distance of 20 km. It is equipped with a RGB (Red, Green and Blue) sensor capable of obtaining 2.8 cm per pixel Ground Sample Distance (GSD) resolution at a constant altitude of 100 m above ground level (AGL). The total cost was $995 which is substantially less than the average value of similar commercial drones used in biodiversity studies. We performed 12 flight tests in auto mode using the developed model in protected areas in Brazil, obtaining RGB images that allowed us to identify deforestation spots smaller than 5 m2 and medium-sized animals. Building DIY drones requires some technical knowledge and demands more time than buying a commercial ready-to-fly system, but as proved here, it can be less expensive, which is often crucial in conservation projects.

Improved individual and population-level HbA1c estimation using CGM data and patient characteristics.

Machine learning and linear regression models using CGM and participant data reduced HbA1c estimation error by up to 26% compared to the GMI formula, and exhibit superior performance in estimating the median of HbA1c at the cohort level, potentially of value for remote clinical trials interrupted by COVID-19.

Challenges in activation of remote monitoring in patients with cardiac rhythm devices during the coronavirus (COVID-19) pandemic.

BACKGROUND: Remote monitoring (RM) technology embedded in cardiac rhythm devices permits continuous monitoring of device function, and recording of selected cardiac physiological parameters and cardiac arrhythmias and may be of utmost utility during Coronavirus (COVID-19) pandemic, when in-person office visit for regular follow-up were postponed. However, patients not alredy followed-up via RM represent a challenging group of patients to be managed during the lockdown. METHODS: We reviewed patient files scheduled for an outpatient visit between January 1, 2020 and May 11th, 2020 to assess the proportion of patients in whom RM activation was possible without office visit, and compared them to those scheduled for visit before the lockdown. RESULTS: During COVID-19 pandemic, RM activation was feasible in a minority of patients (7.8% of patients) expected at outpatient clinic for a follow-up visit and device check-up. This was possible in a good proportion of complex implantable devices such as cardiac resynchronization therapy and implantable cardioverter defibrillator but only in a minority of patients with a pacemaker the RM function could be activated during the period of restricted access to hospital. CONCLUSIONS: Our experience strongly suggest to consider the systematic activation of RM function at the time of implantation or - by default programming - in all cardiac rhythm management devices.

Impact of COVID-19 lockdown on flash and real-time glucose sensor users with type 1 diabetes in England.

AIMS: People with type 1 diabetes (T1D) face the daily task of implementing self-management strategies to achieve their glycaemic goals. The UK COVID-19 lockdown has had an impact on day-to-day behaviour, which may affect diabetes self-management and outcomes. We assessed whether sensor-based outcomes pre- and during lockdown periods were different in a cohort of glucose sensor users with T1D. METHODS: Data were collected from Freestyle Libre (FSL) or Dexcom G6 sensor users who remotely shared their data with the diabetes clinic web platform. Sensor metrics according to international consensus were analysed and compared between pre-lockdown period and 2 and 3 weeks into lockdown (periods 1 and 2). RESULTS: Two hundred and sixty-nine T1D patients (baseline HbA1c 57 ± 14 mmol/mol) were identified as FSL (n = 190) or Dexcom G6 (n = 79) users. In patients with sensor use > 70% (N = 223), compared to pre-lockdown period percentage TIR 3.9-10 mM (TIR) significantly increased during period 1 (59.6 ± 18.2 vs. 57.5 ± 17.2%, p = 0.002) and period 2 (59.3 ± 18.3 vs. 57.5 ± 17.2%, p = 0.035). The proportion of patients achieving TIR ≥ 70% increased from 23.3% pre-lockdown to 27.8% in period 1 and 30.5% in period 2. A higher proportion also achieved the recommended time below and above range, and coefficient of variation in periods 1 and 2. Dexcom G6 users had significantly lower % time below range (< 3.9 mM) compared to FSL users during both lockdown periods (period 1: Dexcom G6 vs. FSL: 1.8% vs. 4%; period 2: 1.4% vs. 4%, p < 0.005 for both periods). CONCLUSION: Sensor-based glycaemic outcomes in people with T1D in the current cohort improved during COVID-19 lockdown, which may be associated with positive changes in self-management strategies. Further work is required to evaluate long-term sustainability and support.

The Promise of Smartphone Applications in the Remote Monitoring of Postsurgical Wounds: A Literature Review.

OBJECTIVE: To review the clinical and scientific literature on remote monitoring and management of postsurgical wounds using smartphone applications (apps). DATA SOURCES: MEDLINE, PubMed, EMBASE, and Cochrane libraries were searched for relevant articles on patients who received surgery and were monitored postdischarge via an app. STUDY SELECTION: Articles were selected with the terms "mobile phones," "smartphones," "wounds," "monitor," and "patient preference." DATA EXTRACTION: The authors found 276 review articles related to telemedicine in wound care. Investigators reviewed the titles and abstracts of the search results and selected 83 articles that were relevant to the remote monitoring of wounds using smartphone apps. DATA SYNTHESIS: The topics explored in selected literature included smartphone app importance to telemedicine, benefits (medical and financial), app examples, and challenges in the context of wound monitoring and management. The authors identified several challenges and limitations that future studies in the field need to address. CONCLUSIONS: Remote monitoring and management of wounds using smartphone apps is a valuable technique to enhance the quality of and access to healthcare. However, although some patients may prefer this technology, some lack technological competence, limiting telemedicine's applicability. In addition, issues remain with the reliable interpretation of data collected through apps.

Ground-level Unmanned Aerial System Imagery Coupled with Spatially Balanced Sampling and Route Optimization to Monitor Rangeland Vegetation.

Rangeland ecosystems cover 3.6 billion hectares globally with 239 million hectares located in the United States. These ecosystems are critical for maintaining global ecosystem services. Monitoring vegetation in these ecosystems is required to assess rangeland health, to gauge habitat suitability for wildlife and domestic livestock, to combat invasive weeds, and to elucidate temporal environmental changes. Although rangeland ecosystems cover vast areas, traditional monitoring techniques are often time-consuming and cost-inefficient, subject to high observer bias, and often lack adequate spatial information. Image-based vegetation monitoring is faster, produces permanent records (i.e., images), may result in reduced observer bias, and inherently includes adequate spatial information. Spatially balanced sampling designs are beneficial in monitoring natural resources. A protocol is presented for implementing a spatially balanced sampling design known as balanced acceptance sampling (BAS), with imagery acquired from ground-level cameras and unmanned aerial systems (UAS). A route optimization algorithm is used in addition to solve the 'travelling salesperson problem' (TSP) to increase time and cost efficiency. While UAS images can be acquired 2-3x faster than handheld images, both types of images are similar to each other in terms of accuracy and precision. Lastly, the pros and cons of each method are discussed and examples of potential applications for these methods in other ecosystems are provided.

A field evaluation of long-term effects of PIT tagging.

Passive integrated transponder (PIT)-tagging is commonly used in behavioural studies of fish, although long-term evaluations of effects from tagging under natural conditions are scarce. We PIT-tagged common bream Abramis brama, European perch Perca fluviatilis, pike Esox lucius and roach Rutilus rutilus, released them in their lakes of origin and recaptured them after 103-3269 days. Overall, tagged fish did not differ in condition from non-tagged fish, except for small R. rutilus that had a lower length-specific body mass in one lake in 1 year. We conclude that PIT-tagging in general has negligible long-term effects on fish condition.

Considerations for development of an evidence dossier to support the use of mobile sensor technology for clinical outcome assessments in clinical trials.

BACKGROUND: Mobile sensors offer enormous potential for the collection of informative clinical endpoints in clinical trials to support regulatory decision making and product labelling. There are currently no specific guidelines on the information needed to enable regulators to review and accept proposed endpoints derived from mobile sensors for use in drug development trials. OBJECTIVE: The purpose of this working group report is to recommend the structure and content of an evidence dossier intended to support whether a clinical endpoint derived from mobile sensor data is fit-for-purpose for use in regulatory submissions for drug approvals. EVIDENCE DOSSIER: The structure and content of a dossier to provide evidence supporting the use of a sensor-derived clinical endpoint is described. Sections include clinical endpoint definition and positioning, the concept of interest, the context of use, clinical validation and interpretation, study implementation, and analytical validity with sensor performance verification in support of the selected sensor. CONCLUSIONS: In the absence of definitive regulatory guidance, this report provides a considered approach to compiling a comprehensive body of evidence to justify acceptance of mobile sensors for support of new drug applications.

Digital pathology for intraoperative frozen section diagnosis of thoracic specimens: an evaluation of a system using remote sampling and whole slide imaging diagnosis.

BACKGROUND: Digital pathology is now used for primary diagnostic work as well as teaching, research and consultation. In our multisite institution service reorganisation led to histopathology being located in a separate hospital from some surgical specialities. We implemented remotely supervised specimen sampling and frozen section diagnosis using digital pathology. In this study we assessed the concordance of glass and digital slide diagnosis using this system. METHODS: We reviewed cases from the first 2 years of digital frozen section reporting at our institution. Cases with potential digital to glass slide discordance were reviewed by three experienced thoracic histopathologists. The reasons for discordance were determined and common themes identified. We also reviewed critical incidents relating to digital pathology during the study period. RESULTS: The study population comprised 211 cases. Frozen section to final diagnosis concordance between digital and glass slide diagnosis was found in 196 (92.6%) cases. The 15 potentially discordant cases were reviewed. Intraobserver concordance between glass and digital slide review ranged from 9/15 to 12/15 cases across the three pathologists. Glass slide review diagnosis showed better concordance with ground truth in two cases; digital slide review was more accurate in two cases. One relevant critical incident was identified during the study period. DISCUSSION: This is the largest study to examine digital pathology for thoracic frozen section diagnosis and shows that this is a safe and feasible alternative to glass slide diagnosis. Discordance between digital and glass slide diagnoses were unrelated to the processes of whole slide imaging and digital microscopy.

A novel ε-sensitive correlation indistinguishable scheme for publishing location data.

Nowadays, location based service (LBS) is one of the most popular mobile apps and following with humongous of location data been produced. The publishing of location data can provide benefit for promoting the quality of service, optimizing the commercial environment as well as harmonizing the infrastructure construction. However, as location data may contain some sensitive or confidential information, the publishing may reveal privacy and bring hazards. So the published data had to be disposed to protect the privacy. In order to cope with this problem, a number of algorithms based on the strategy of k-anonymity were proposed, but this is not enough for the privacy protection, as the correlation between the sensitive region and the background knowledge can be used to infer the real location. Thus, consider about this condition, in this paper a ε-sensitive correlation privacy protection scheme is proposed, and provides correlation indistinguishable to the location data. In this scheme, entropy is first used to determine the location centroid of each cell to build up the voronoi diagram. Then the coordinate of the untreated location data that is located in the cell is transferred into the centroid vicinity. Accordingly, the sensitive correlation is destroyed by the coordinate of each published data. The process of transferring the location data is determined by metrics of ε-sensitive correlation privacy, and is rigorous in mathematical justification. At last, security analysis is proposed in this paper to verify the privacy ability of our proposed algorithm based on voronoi diagram and entropy, and then we utilize the comparative experiment to further affirm the advantage of this algorithm in the location data privacy protection as well as the availability of published data.

Cyber Attacks on Healthcare Devices Using Unmanned Aerial Vehicles.

The growing use of wireless technology in healthcare systems and devices makes these systems particularly open to cyber-based attacks, including denial of service and information theft via sniffing (eaves-dropping) and phishing attacks. Evolving technology enables wireless healthcare systems to communicate over longer ranges, which opens them up to greater numbers of possible threats. Unmanned aerial vehicles (UAV) or drones present a new and evolving attack surface for compromising wireless healthcare systems. An enumeration of the types of wireless attacks capable via drones are presented, including two new types of cyber threats: a stepping stone attack and a cloud-enabled attack. A real UAV is developed to test and demonstrate the vulnerabilities of healthcare systems to this new threat vector. The UAV successfully attacked a simulated smart hospital environment and also a small collection of wearable healthcare sensors. Compromise of wearable or implanted medical devices can lead to increased morbidity and mortality.

Convolutional Neural Networks enable efficient, accurate and fine-grained segmentation of plant species and communities from high-resolution UAV imagery.

Recent technological advances in remote sensing sensors and platforms, such as high-resolution satellite imagers or unmanned aerial vehicles (UAV), facilitate the availability of fine-grained earth observation data. Such data reveal vegetation canopies in high spatial detail. Efficient methods are needed to fully harness this unpreceded source of information for vegetation mapping. Deep learning algorithms such as Convolutional Neural Networks (CNN) are currently paving new avenues in the field of image analysis and computer vision. Using multiple datasets, we test a CNN-based segmentation approach (U-net) in combination with training data directly derived from visual interpretation of UAV-based high-resolution RGB imagery for fine-grained mapping of vegetation species and communities. We demonstrate that this approach indeed accurately segments and maps vegetation species and communities (at least 84% accuracy). The fact that we only used RGB imagery suggests that plant identification at very high spatial resolutions is facilitated through spatial patterns rather than spectral information. Accordingly, the presented approach is compatible with low-cost UAV systems that are easy to operate and thus applicable to a wide range of users.

Aerial surveys cause large but ephemeral decreases in bear presence at salmon streams in Kodiak, Alaska.

Aerial surveys are often used to monitor wildlife and fish populations, but rarely are the effects on animal behavior documented. For over 30 years, the Kodiak National Wildlife Refuge has conducted low-altitude aerial surveys to assess Kodiak brown bear (Ursus arctos middendorffi) space use and demographic composition when bears are seasonally congregated near salmon spawning streams in southwestern Kodiak Island, Alaska. Salmon (Oncorhynchus spp.) are an important bear food and salmon runs are brief, so decreases in time spent fishing for salmon may reduce salmon consumption by bears. The goal of this study was to apply different and complementary field methods to evaluate the response of bears to these aerial surveys. Ground-based counts at one stream indicated 62% of bears departed the 200m-wide survey zone in response to aerial surveys, but bear counts returned to pre-survey abundance after only three hours. Although this effect was brief, survey flights occurred during the hours of peak daily bear activity (morning and evening), so the three-hour disruption appeared to result in a 25% decline in cumulative daily detections by 38 time-lapse cameras deployed along 10 salmon streams. Bear responses varied by sex-male bears were much more likely than female bears (with or without cubs) to depart streams and female bears with GPS collars did not move from streams following surveys. Although bears displaced by aerial surveys may consume fewer salmon, the actual effect on their fitness depends on whether they compensate by foraging at other times or by switching to other nutritious resources. Data from complementary sources allows managers to more robustly understand the impacts of surveys and whether their benefits are justified. Similar assessments should be made on alternative techniques such as Unmanned Aerial Vehicles and non-invasive sampling to determine whether they supply equivalent data while limiting bear disturbance.

Remote Surveillance Technologies: Realizing the Aim of Right Patient, Right Data, Right Time.

The convergence of multiple recent developments in health care information technology and monitoring devices has made possible the creation of remote patient surveillance systems that increase the timeliness and quality of patient care. More convenient, less invasive monitoring devices, including patches, wearables, and biosensors, now allow for continuous physiological data to be gleaned from patients in a variety of care settings across the perioperative experience. These data can be bound into a single data repository, creating so-called data lakes. The high volume and diversity of data in these repositories must be processed into standard formats that can be queried in real time. These data can then be used by sophisticated prediction algorithms currently under development, enabling the early recognition of patterns of clinical deterioration otherwise undetectable to humans. Improved predictions can reduce alarm fatigue. In addition, data are now automatically queriable on a real-time basis such that they can be fed back to clinicians in a time frame that allows for meaningful intervention. These advancements are key components of successful remote surveillance systems. Anesthesiologists have the opportunity to be at the forefront of remote surveillance in the care they provide in the operating room, postanesthesia care unit, and intensive care unit, while also expanding their scope to include high-risk preoperative and postoperative patients on the general care wards. These systems hold the promise of enabling anesthesiologists to detect and intervene upon changes in the clinical status of the patient before adverse events have occurred. Importantly, however, significant barriers still exist to the effective deployment of these technologies and their study in impacting patient outcomes. Studies demonstrating the impact of remote surveillance on patient outcomes are limited. Critical to the impact of the technology are strategies of implementation, including who should receive and respond to alerts and how they should respond. Moreover, the lack of cost-effectiveness data and the uncertainty of whether clinical activities surrounding these technologies will be financially reimbursed remain significant challenges to future scale and sustainability. This narrative review will discuss the evolving technical components of remote surveillance systems, the clinical use cases relevant to the anesthesiologist's practice, the existing evidence for their impact on patients, the barriers that exist to their effective implementation and study, and important considerations regarding sustainability and cost-effectiveness.

Smart Home-based IoT for Real-time and Secure Remote Health Monitoring of Triage and Priority System using Body Sensors: Multi-driven Systematic Review.

The Internet of Things (IoT) has been identified in various applications across different domains, such as in the healthcare sector. IoT has also been recognised for its revolution in reshaping modern healthcare with aspiring wide range prospects, including economical, technological and social. This study aims to establish IoT-based smart home security solutions for real-time health monitoring technologies in telemedicine architecture. A multilayer taxonomy is driven and conducted in this study. In the first layer, a comprehensive analysis on telemedicine, which focuses on the client and server sides, shows that other studies associated with IoT-based smart home applications have several limitations that remain unaddressed. Particularly, remote patient monitoring in healthcare applications presents various facilities and benefits by adopting IoT-based smart home technologies without compromising the security requirements and potentially large number of risks. An extensive search is conducted to identify articles that handle these issues, related applications are comprehensively reviewed and a coherent taxonomy for these articles is established. A total number of (n = 3064) are gathered between 2007 and 2017 for most reliable databases, such as ScienceDirect, Web of Science and Institute of Electrical and Electronic Engineer Xplore databases. Then, the articles based on IoT studies that are associated with telemedicine applications are filtered. Nine articles are selected and classified into two categories. The first category, which accounts for 22.22% (n = 2/9), includes surveys on telemedicine articles and their applications. The second category, which accounts for 77.78% (n = 7/9), includes articles on the client and server sides of telemedicine architecture. The collected studies reveal the essential requirement in constructing another taxonomy layer and review IoT-based smart home security studies. Therefore, IoT-based smart home security features are introduced and analysed in the second layer. The security of smart home design based on IoT applications is an aspect that represents a crucial matter for general occupants of smart homes, in which studies are required to provide a better solution with patient security, privacy protection and security of users' entities from being stolen or compromised. Innovative technologies have dispersed limitations related to this matter. The existing gaps and trends in this area should be investigated to provide valuable visions for technical environments and researchers. Thus, 67 articles are obtained in the second layer of our taxonomy and are classified into six categories. In the first category, 25.37% (n = 17/67) of the articles focus on architecture design. In the second category, 17.91% (n = 12/67) includes security analysis articles that investigate the research status in the security area of IoT-based smart home applications. In the third category, 10.44% (n = 7/67) includes articles about security schemes. In the fourth category, 17.91% (n = 12/67) comprises security examination. In the fifth category, 13.43% (n = 9/67) analyses security protocols. In the final category, 14.92% (n = 10/67) analyses the security framework. Then, the identified basic characteristics of this emerging field are presented and provided in the following aspects. Open challenges experienced on the development of IoT-based smart home security are addressed to be adopted fully in telemedicine applications. Then, the requirements are provided to increase researcher's interest in this study area. On this basis, a number of recommendations for different parties are described to provide insights on the next steps that should be considered to enhance the security of smart homes based on IoT. A map matching for both taxonomies is developed in this study to determine the novel risks and benefits of IoT-based smart home security for real-time remote health monitoring within client and server sides in telemedicine applications.

Sensor-Based mHealth Authentication for Real-Time Remote Healthcare Monitoring System: A Multilayer Systematic Review.

The new and groundbreaking real-time remote healthcare monitoring system on sensor-based mobile health (mHealth) authentication in telemedicine has considerably bounded and dispersed communication components. mHealth, an attractive part in telemedicine architecture, plays an imperative role in patient security and privacy and adapts different sensing technologies through many built-in sensors. This study aims to improve sensor-based defence and attack mechanisms to ensure patient privacy in client side when using mHealth. Thus, a multilayer taxonomy was conducted to attain the goal of this study. Within the first layer, real-time remote monitoring studies based on sensor technology for telemedicine application were reviewed and analysed to examine these technologies and provide researchers with a clear vision of security- and privacy-based sensors in the telemedicine area. An extensive search was conducted to find articles about security and privacy issues, review related applications comprehensively and establish the coherent taxonomy of these articles. ScienceDirect, IEEE Xplore and Web of Science databases were investigated for articles on mHealth in telemedicine-based sensor. A total of 3064 papers were collected from 2007 to 2017. The retrieved articles were filtered according to the security and privacy of sensor-based telemedicine applications. A total of 19 articles were selected and classified into two categories. The first category, 57.89% (n = 11/19), included survey on telemedicine articles and their applications. The second category, 42.1% (n = 8/19), included articles contributed to the three-tiered architecture of telemedicine. The collected studies improved the essential need to add another taxonomy layer and review the sensor-based smartphone authentication studies. This map matching for both taxonomies was developed for this study to investigate sensor field comprehensively and gain access to novel risks and benefits of the mHealth security in telemedicine application. The literature on sensor-based smartphones in the second layer of our taxonomy was analysed and reviewed. A total of 599 papers were collected from 2007 to 2017. In this layer, we obtained a final set of 81 articles classified into three categories. The first category of the articles [86.41% (n = 70/81)], where sensor-based smartphones were examined by utilising orientation sensors for user authentication, was used. The second category [7.40% (n = 6/81)] included attack articles, which were not intensively included in our literature analysis. The third category [8.64% (n = 7/81)] included 'other' articles. Factors were considered to understand fully the various contextual aspects of the field in published studies. The characteristics included the motivation and challenges related to sensor-based authentication of smartphones encountered by researchers and the recommendations to strengthen this critical area of research. Finally, many studies on the sensor-based smartphone in the second layer have focused on enhancing accurate authentication because sensor-based smartphones require sensors that could authentically secure mHealth.

Analysis and Improvement of a Mutual Authentication Scheme for Wireless Body Area Networks.

An increase in aging population and the consequent chronic diseases pose not only serious effects to the economy but also a heavy burden to the medical system. Wireless body area networks (WBANs) provide a simple and low-cost strategy for health monitoring and telemedicine of the elderly. Many authentication schemes based on WBAN have been presented to address the sensitivity and privacy of collected data and the open characteristic of wireless networks. Wu et al. recently presented an efficient anonymous authentication scheme for WBANs, in which a one-side bilinear pairing methodology was applied to reduce the burden on the WBAN client side. However, we demonstrate that their scheme suffers from client impersonation attacks and that the adversary can easily forge a legal client to access the network service. In this paper, we analyze the limitations of Wu et al.'s scheme and design a novel mutual authentication scheme for WBANs that adopt asymmetric bilinear pairing to enhance security. Results of security and performance analyses reveal that the new scheme offers more effective security, better performance, and higher efficiency than Wu et al.'s scheme. We also provide a formal security proof of the protocol by using BAN authentication logic.