Internet of Things (IoT) is a worldwide system of "smart devices" that can sense and connect with their surroundings and interact with users and other systems. Global air pollution is one of the ...major concerns of our era. Existing monitoring systems have inferior precision, low sensitivity, and require laboratory analysis. Therefore, improved monitoring systems are needed. To overcome the problems of existing systems, we propose a three-phase air pollution monitoring system. An IoT kit was prepared using gas sensors, Arduino integrated development environment (IDE), and a Wi-Fi module. This kit can be physically placed in various cities to monitoring air pollution. The gas sensors gather data from air and forward the data to the Arduino IDE. The Arduino IDE transmits the data to the cloud via the Wi-Fi module. We also developed an Android application termed IoT-Mobair , so that users can access relevant air quality data from the cloud. If a user is traveling to a destination, the pollution level of the entire route is predicted, and a warning is displayed if the pollution level is too high. The proposed system is analogous to Google traffic or the navigation application of Google Maps. Furthermore, air quality data can be used to predict future air quality index (AQI) levels.
Continuous glucose monitoring (CGM) provides real-time assessment of glucose levels and may be beneficial in reducing hypoglycemia in older adults with type 1 diabetes.
To determine whether CGM is ...effective in reducing hypoglycemia compared with standard blood glucose monitoring (BGM) in older adults with type 1 diabetes.
Randomized clinical trial conducted at 22 endocrinology practices in the United States among 203 adults at least 60 years of age with type 1 diabetes.
Participants were randomly assigned in a 1:1 ratio to use CGM (n = 103) or standard BGM (n = 100).
The primary outcome was CGM-measured percentage of time that sensor glucose values were less than 70 mg/dL during 6 months of follow-up. There were 31 prespecified secondary outcomes, including additional CGM metrics for hypoglycemia, hyperglycemia, and glucose control; hemoglobin A1c (HbA1c); and cognition and patient-reported outcomes, with adjustment for multiple comparisons to control for false-discovery rate.
Of the 203 participants (median age, 68 interquartile range {IQR}, 65-71 years; median type 1 diabetes duration, 36 IQR, 25-48 years; 52% female; 53% insulin pump use; mean HbA1c, 7.5% SD, 0.9%), 83% used CGM at least 6 days per week during month 6. Median time with glucose levels less than 70 mg/dL was 5.1% (73 minutes per day) at baseline and 2.7% (39 minutes per day) during follow-up in the CGM group vs 4.7% (68 minutes per day) and 4.9% (70 minutes per day), respectively, in the standard BGM group (adjusted treatment difference, -1.9% (-27 minutes per day); 95% CI, -2.8% to -1.1% -40 to -16 minutes per day; P <.001). Of the 31 prespecified secondary end points, there were statistically significant differences for all 9 CGM metrics, 6 of 7 HbA1c outcomes, and none of the 15 cognitive and patient-reported outcomes. Mean HbA1c decreased in the CGM group compared with the standard BGM group (adjusted group difference, -0.3%; 95% CI, -0.4% to -0.1%; P <.001). The most commonly reported adverse events using CGM and standard BGM, respectively, were severe hypoglycemia (1 and 10), fractures (5 and 1), falls (4 and 3), and emergency department visits (6 and 8).
Among adults aged 60 years or older with type 1 diabetes, continuous glucose monitoring compared with standard blood glucose monitoring resulted in a small but statistically significant improvement in hypoglycemia over 6 months. Further research is needed to understand the long-term clinical benefit.
ClinicalTrials.gov Identifier: NCT03240432.
We provide a broad overview of the underlying philosophy of ecological monitoring. We argue that the major characteristics of effective monitoring programs typically include: (1) Good questions. (2) ...A conceptual model of an ecosystem or population. (3) Strong partnerships between scientists, policy-makers and managers. (4) Frequent use of data collected.
We classify monitoring programs into three categories – (1) Passive monitoring, which is devoid of specified questions or underlying study design and has limited rationale other than curiosity. (2) Mandated monitoring where environmental data are gathered as a stipulated requirement of government legislation or a political directive. The focus is usually to identify trends. (3) Question-driven monitoring, which is guided by a conceptual model and by a rigorous design that will typically result in a priori predictions that can be tested.
There are advantages and disadvantages of mandated monitoring programs, which are typically large-scaled, and generally smaller-scaled, question-driven monitoring programs. For example, while question-driven monitoring programs can provide insights into the ecological processes giving rise to emergent environmental patterns, spatial generalization from them is difficult because results may not extrapolate well to other regions, states or to a national level. Conversely, while mandated monitoring can be useful for producing coarse level summaries of temporal changes in a target population or resource condition they may not identify the mechanism influencing a change in an ecosystem or an entity. A key remaining challenge is to develop much improved mandated monitoring programs through more widespread adoption of the features of successful question-driven monitoring programs in efforts to enhance biodiversity conservation and environmental management.
People with type 1 diabetes can continuously monitor their glucose levels on demand (intermittently scanned continuous glucose monitoring isCGM), or in real time (real-time continuous glucose ...monitoring rtCGM). However, it is unclear whether switching from isCGM to rtCGM with alert functionality offers additional benefits. Therefore, we did a trial comparing rtCGM and isCGM in adults with type 1 diabetes (ALERTT1).
We did a prospective, double-arm, parallel-group, multicentre, randomised controlled trial in six hospitals in Belgium. Adults with type 1 diabetes who previously used isCGM were randomly assigned (1:1) to rtCGM (intervention) or isCGM (control). Randomisation was done centrally using minimisation dependent on study centre, age, gender, glycated haemoglobin (HbA1c), time in range (sensor glucose 3·9–10·0 mmol/L), insulin administration method, and hypoglycaemia awareness. Participants, investigators, and study teams were not masked to group allocation. Primary endpoint was mean between-group difference in time in range after 6 months assessed in the intention-to-treat sample. This trial is registered with ClinicalTrials.gov, NCT03772600.
Between Jan 29 and Jul 30, 2019, 269 participants were recruited, of whom 254 were randomly assigned to rtCGM (n=127) or isCGM (n=127); 124 and 122 participants completed the study, respectively. After 6 months, time in range was higher with rtCGM than with isCGM (59·6% vs 51·9%; mean difference 6·85 percentage points 95% CI 4·36–9·34; p<0·0001). After 6 months HbA1c was lower (7·1% vs 7·4%; p<0·0001), as was time <3·0 mmol/L (0·47% vs 0·84%; p=0·0070), and Hypoglycaemia Fear Survey version II worry subscale score (15·4 vs 18·0; p=0·0071). Fewer participants on rtCGM experienced severe hypoglycaemia (n=3 vs n=13; p=0·0082). Skin reaction was more frequently observed with isCGM and bleeding after sensor insertion was more frequently reported by rtCGM users.
In an unselected adult type 1 diabetes population, switching from isCGM to rtCGM significantly improved time in range after 6 months of treatment, implying that clinicians should consider rtCGM instead of isCGM to improve the health and quality of life of people with type 1 diabetes.
Dexcom.
Engineered structures in the open ocean are becoming more frequent with the expansion of the marine renewable energy industry and offshore marine aquaculture. Floating engineered structures function ...as artificial patch reefs providing novel and relatively stable habitat structure not otherwise available in the pelagic water column. The enhanced physical structure can increase local biodiversity and benefit fisheries yet can also facilitate the spread of invasive species. Clear evidence of any ecological consequences will inform the design and placement of structures to either minimise negative impacts or enhance ecosystem restoration. The development of rapid, cost-effective and reliable remote underwater monitoring methods is crucial to supporting evidence-based decision-making by planning authorities and developers when assessing environmental risks and benefits of offshore structures. A novel, un-baited midwater video system,
PelagiCam
, with motion-detection software (MotionMeerkat) for semi-automated monitoring of mobile marine fauna, was developed and tested on the UK’s largest offshore rope-cultured mussel farm in Lyme Bay, southwest England.
PelagiCam
recorded Atlantic horse mackerel (
Trachurus trachurus
), garfish (
Belone belone
) and two species of jellyfish (
Chrysaora hysoscella
and
Rhizostoma pulmo
) in open water close to the floating farm structure. The software successfully distinguished video frames where fishes were present versus absent. The
PelagiCam
system provides a cost-effective remote monitoring tool to streamline biological data acquisition in impact assessments of offshore floating structures. With the rise of sophisticated artificial intelligence for object recognition, the integration of computer vision techniques should receive more attention in marine ecology and has great potential to revolutionise marine biological monitoring.
•AE mechanisms in RE systems were firstly classified.•AE sensors, signal processing and fault diagnosis and leading advances across representative RE fields were summarized.•Challenges and ...development trends of AE in RE systems were proposed.
Renewable energy (RE) does not pollute environment at the point of energy generation, and generally has a much lower pollution footprint than traditional energy from installing to decommissioning, and can diversify the power generation technology. Because of the high operation and maintenance (O&M) costs, it is necessary to build remote, online, credible monitoring and inspection techniques. Acoustic emission (AE) technology is effective and efficient to monitor and detect mechanical damage, deterioration, and failure, etc. Over the recent years, a remarkable number of scientific papers demonstrate the capability of AE in nondestructive testing (NDT), structure health monitoring (SHM), condition monitoring (CM) and fault diagnosis for RE generation, transmission, transformation and storage systems. Most of work focusing on detection principle, sensor design, signal processing and diagnosis has provided a lot of valuable contributions for academic and industrial fields. Nevertheless, all this valuable information is scattered over many sub-fields of literature, and the knowledge is not systematic. This paper is dedicated to analyze the different AE principles in RE systems, and to comprehensively summarize and clearly highlight the advanced methods and challenges. Development trends in research, application and standard are also discussed and suggested.
Over the past decade, a range of sensor technologies became available on the market, enabling a revolutionary shift in air pollution monitoring and assessment. With their cost of up to three orders ...of magnitude lower than standard/reference instruments, many avenues for applications have opened up. In particular, broader participation in air quality discussion and utilisation of information on air pollution by communities has become possible. However, many questions have been also asked about the actual benefits of these technologies. To address this issue, we conducted a comprehensive literature search including both the scientific and grey literature. We focused upon two questions: (1) Are these technologies fit for the various purposes envisaged? and (2) How far have these technologies and their applications progressed to provide answers and solutions? Regarding the former, we concluded that there is no clear answer to the question, due to a lack of: sensor/monitor manufacturers' quantitative specifications of performance, consensus regarding recommended end-use and associated minimal performance targets of these technologies, and the ability of the prospective users to formulate the requirements for their applications, or conditions of the intended use. Numerous studies have assessed and reported sensor/monitor performance under a range of specific conditions, and in many cases the performance was concluded to be satisfactory. The specific use cases for sensors/monitors included outdoor in a stationary mode, outdoor in a mobile mode, indoor environments and personal monitoring. Under certain conditions of application, project goals, and monitoring environments, some sensors/monitors were fit for a specific purpose. Based on analysis of 17 large projects, which reached applied outcome stage, and typically conducted by consortia of organizations, we observed that a sizable fraction of them (~ 30%) were commercial and/or crowd-funded. This fact by itself signals a paradigm change in air quality monitoring, which previously had been primarily implemented by government organizations. An additional paradigm-shift indicator is the growing use of machine learning or other advanced data processing approaches to improve sensor/monitor agreement with reference monitors. There is still some way to go in enhancing application of the technologies for source apportionment, which is of particular necessity and urgency in developing countries. Also, there has been somewhat less progress in wide-scale monitoring of personal exposures. However, it can be argued that with a significant future expansion of monitoring networks, including indoor environments, there may be less need for wearable or portable sensors/monitors to assess personal exposure. Traditional personal monitoring would still be valuable where spatial variability of pollutants of interest is at a finer resolution than the monitoring network can resolve.
•Extensive review of low-cost sensing technologies for air quality monitoring.•Low-cost sensors were considered fit for many specific purposes.•The technologies helped to expand the conversations with communities.•More works are required to achieve the full potential of the technologies.
Electromagnetic radars have been shown potentially to be used for remote sensing of biosignals in a more comfortable and easier way than wearable and contact devices. While there is an increasing ...interest in using radars for health monitoring, their performance has not been tested and reported either in practical scenarios or with acceptable low errors. Therefore, we use a frequency modulated continuous wave (FMCW) radar operating at 77 GHz in a bedroom environment to extract the respiration and heart rates of a patient, who is used to lying down on the bed. Indeed, the proposed signal processing contains advanced phase unwrapping manipulation, which is unique. In addition, the results are compared with a reliable reference sensor. Our results show that the correlations between the reference sensor and the radar estimates are in 94% and 80% for breathing and heart rates, respectively.
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