Alert System Research Articles

STRAUMA: A Novel Alert System for a Combined Stroke and Trauma.

Cerebrovascular accident (CVA) can lead to traumatic injury. While timely administration of tissue plasminogen activator (tPA) can be lifesaving in CVAs, it is contraindicated with active bleeding. A STRAUMA is a combined stroke and highest-level trauma activation for patients with suspected CVA and signs of trauma. The purpose of this study is to evaluate the impact of the STRAUMA activation on time to CT and patient outcomes. A retrospective review was conducted on adult patients presenting to a Level 1 trauma and comprehensive stroke center with signs of CVA between 01/2019 and 09/2020. Patients who had a STRAUMA activation were compared to patients who had a stroke alert. Five hundred and eighty patients met the inclusion criteria. Of these, 111 had STRAUMA activations and 469 had stroke alerts. There were no differences in age, gender, or anticoagulation use. The STRAUMA group had a higher NIH stroke scale (NIHSS) (11 vs 5, P<.0001). The STRAUMA group had a longer time to CT (23.1 min vs 16.9 min, P<.0001) and a lower rate of tPA (13.5% vs 27.9%, P = .001). Time to tPA and thrombectomy were similar. The STRAUMA group had a 15% rate of traumatic injury with a median injury severity score of 9. Mortality was higher in the STRAUMA group (14.4% vs 6.0%, P = .003). Multivariable logistic regression identified NIHSS and time to CT as predictors of mortality. STRAUMA did not predict mortality. The novel STRAUMA activation allows for an evaluation of both stroke and trauma to facilitate safe and timely administration of lifesaving interventions.

Smart Agriculture Monitoring &amp; Auto Irrigation System using IoT with ESP8266

Abstract: In this paper, an IoT-based smart agriculture monitoring and automatic irrigation system are proposed by using ESP8266 Node MCU. Multiple sensors like capacitive soil moisture sensors are fixed inside to measure moisture content present in the soil which will help in the auto-detection of water requisition in the soil. DS18B20 waterproof temperature sensor will measure the temperature of the soil. The DHT22 is used as a humidity and temperature sensor to measure the air temperature and humidity. Soil relative humidity, air temperature, soil temperature, and relative humidity of air are also measured. A small OLED Display is used which is 0.96 inches in size. If any unwanted intrusion by animals or humans is detected on the farm, a PIR motion sensor is used to detect their motion activity. A rain detector sensor is used to detect rain status. A 5 Volt buzzer is for the Alert system and a 5-volt power relay is to control the water pump, whenever a low quantity of moisture is detected in the soil. Overall by using these farming systems users get more benefits and good results from their farming.

Analysis of RASFF notifications on cereals and cereal-based products contaminated with mycotoxins in the period from 01/01/2015 to 31/12/2019

The Rapid Alert System for Food and Feed (RASFF) is designed to respond promptly to the health risks associated with food, food contact materials or feed by enabling fast exchange of information between bodies and institutions involved in the system. Mycotoxins, secondary metabolites produced by moulds, are common contaminants found in cereals and cereal-based product all over the world that can be harmful to human (and animal) health. The aim of this study was to analyse RASFF notifications on cereals and cereal-based products contaminated with mycotoxins in the period from 01/01/2015 to 31/12/2019. All data were downloaded from the RASFF database (RASFF portal) and processed in MS Excel 2010. The collected data provided information on the: notifying country, country(ies) of origin and distribution of the contaminated product, notification basis, notification type, risk decision, distribution status, action taken, type of mycotoxin and specific cereal or cereal-based product in which the mycotoxin has been determined. Nearly half of the reported food products originated from Italy, Pakistan, India, Serbia and Sri Lanka. More than half notifications were published by Germany, Switzerland, Italy and Belgium. Only in less than one-fifth of the notifications the country of origin of the contaminated product was also the notifying country. Contaminated products in more than two-thirds of cases were maize, rice and rye grains and their products. Aflatoxin B1 was the most frequent mycotoxin, present in more than two-fifths of contaminated cereals and cereal-based products. The majority of the notifications were classified as alert notifications and a large majority of total number of notifications were of serious risk. Regarding the distribution status, over two-fifths of contaminated products were distributed to other member countries and in almost half of the notifications contaminated products were withdrawn or recalled.

Insulin Pump-Associated Adverse Events in a Brazilian Reference Center for the Treatment of Diabetes Mellitus: Proposal for a Taxonomy of Device Failures in Adults, Adolescents, and Children.

Since the introduction of continuous subcutaneous insulin infusion (CSII), the benefits have been numerous. However, adverse events (AEs) are experienced by up to 40% of users per year, exposing them to potentially fatal risks. The available evidence on the variables that trigger AEs associated with CSII remains limited, indicating the importance of studies on the subject. To propose a taxonomy based on the prevalent AEs experienced by patients from a reference diabetes mellitus (DM) center in Brazil using different CSII devices. 118 patients participated in an online interview and answered the questions of the data collection instrument. Identifying categories and subcategories of analysis contributed to constructing the AEs taxonomy. The five analysis categories identified were: CSII User Interface (n = 45), CSII Alert System (n = 13), CSII Software and Connection (n = 11), CSII Durability (n = 30), and Electrical and Mechanical System of CSII (n = 60) A total of 159 AEs were identified, including conflicting alert messages and error/warning notification failures, errors resulting from engine malfunctions, data loss, patient interface deficiencies, button problems, and battery failure. The study describes in a taxonomic format the AEs directly associated with the use of modern CSIIs that may contribute with additional information to the Food and Drug Administration (FDA) Medical Device Report (MDR) adverse event codes. In addition to guiding educational actions in the treatment of DM and providing information for health professionals and medical device developers, prospective studies examining the frequency of such problems, including the potential psychosocial impact of this technologically advanced therapy, are needed.

Analysis of RASFF notifications on allergens in cereals and cereal-based products in the period from 01/01/2015 to 31/12/2019

The aim of this study was to analyse RASFF notifications on allergens in cereals and cereal-based products in the period from 01/01/2015 to 31/12/2019. Allergies caused by food intake due to the presence of an allergen can pose a serious danger to the health of consumers. In order to promptly respond to any health risks related to food, food contact materials, or feed, The Rapid Alert System for Food and Feed (RASFF) enables quick information exchange between the bodies and institutions involved in the system. All data on allergens in cereals and cereal-based products were downloaded from the RASFF database (RASFF portal) and processed in MS Excel 2010. The collected data provided information on the: notifying country, country(ies) of origin and distribution of the food product in question, notification basis, notification type, risk decision, distribution status, action taken, allergen present and respective food product. More than half of the reported food products originated from Italy, Germany, United Kingdom and Netherlands. Almost half of notifications were published by United Kingdom, Germany, Italy and Spain. The most common allergens were milk, gluten and soya. Products in question in more than two-fifths of cases were pastry (sweet or savoury). The majority of the notifications were classified as alert notifications and a vast majority of total number of notifications were of serious risk. Allergen notifications were mainly based on official controls on the market and on company's own check but some were based on food poisoning. Just over two-thirds of products in question were distributed to other (member and non-member) countries and in over two-thirds of the notifications products in question were withdrawn or recalled.

Automatic Alert System for Monitoring & Detection of Blockage in Manholes

Automatic Alert System for Monitoring & Detection of Blockage in Manholes

AI Enabled Accident Detection and Alert System Using IoT and Deep Learning for Smart Cities

As the number of vehicles increases, road accidents are on the rise every day. According to the World Health Organization (WHO) survey, 1.4 million people have died, and 50 million people have been injured worldwide every year. The key cause of death is the unavailability of medical care at the accident site or the high response time in the rescue operation. A cognitive agent-based collision detection smart accident alert and rescue system will help us to minimize delays in a rescue operation that could save many lives. With the growing popularity of smart cities, intelligent transportation systems (ITS) are drawing major interest in academia and business, and are considered as a means to improve road safety in smart cities. This article proposed an intelligent accident detection and rescue system which mimics the cognitive functions of the human mind using the Internet of Things (IoTs) and the Artificial Intelligence system (AI). An IoT kit is developed that detects the accident and collects all accident-related information, such as position, pressure, gravitational force, speed, etc., and sends it to the cloud. In the cloud, once the accident is detected, a deep learning (DL) model is used to validate the output of the IoT module and activate the rescue module. Once the accident is detected by the DL module, all the closest emergency services such as the hospital, police station, mechanics, etc., are notified. Ensemble transfer learning with dynamic weights is used to minimize the false detection rate. Due to the dataset’s unavailability, a personalized dataset is generated from the various videos available on the Internet. The proposed method is validated by a comparative analysis of ResNet and InceptionResnetV2. The experiment results show that InceptionResnetV2 provides a better performance compared to ResNet with training, validation, and a test accuracy of 98%, respectively. To measure the performance of the proposed approach in the real world, it is validated on the toy car.

Social Distancing Measurement and Alert System Equipment

Social Distancing Measurement and Alert System Equipment

Listeria prevention

<i>Listeria</i> prevention

Fire Sense

Abstract: The significance of putting out a fire as soon as possible can serve to warn others about the perils of disaster and death. Common sensor fire detection systems are limited, especially in a vast location, requiring a long time to detect a fire, and are unable to work in an open environment. This study developed a fire sense approach based on visual sensitivity and colourful variables such as colour, earth filling, light, backdrop, and fire detection time to assess the likelihood of a fire. The degree of error of fire detection was calculated in this study’s test. Keywords: Fire Detection, HSV, Time Frame Selection, Alert System, Fire Alarm

IOT Based Flood Detection and Alert System

Flood is a naturally occurring phenomenon that has gained international attention due to its destructive influence on civilization. Flooding episodes are not going to change, but their impact on mankind can be significantly minimized. The goal of this project is to provide warnings to flood-prone communities. Our project comprises of a water monitoring system that serves as a prototype for flood detection. Flood warnings are used to identify and anticipate potentially dangerous flood occurrences so that the nearby areas can be warned ahead of time. Sensors, GSM, and Wi-Fi modules will be useful in providing flood information. The warning system in this suggested design would use sensors to monitor dams for flood status, and the information will be delivered via the Wi-Fi module. Flood occurrences are effectively observed in real time, giving people plenty of time to prepare for floods that are expected. This approach may be used to drastically minimize the number of people killed or injured in the case of catastrophic flood.

Behaviour and adhesion capacity of Listeria monocytogenes on Mozzarella di Bufala Campana PDO cheese and in fluids involved in the production process

Listeria monocytogenes is a foodborne pathogen for humans. It can be found in ready-to-eat (RTE) products and its presence represents one of the biggest food safety concerns. Most of the cases of cheese contamination reported by the Rapid Alert System for Food and Feed (RASFF) in the last 10 years did not involve Mozzarella di Bufala Campana (MBC) Protected Designation of Origin (PDO) cheese. Suddenly, in the last years, RASFF has disposed of the withdrawn from the market of this product contaminated with L. monocytogenes on two different occasions (RASFF 2018/1198 and 2018/2459), and the Canadian Food Inspection Agency disposed one withdrawn in 2019. Following these events, this study aimed to evaluate the behaviour of L. monocytogenes in Mozzarella di Bufala Campana PDO cheese. First of all, the adhesion capacity of the pathogen to MBC cheese was studied through microbial challenge tests simulating the passage of MBC in hardening water and in covering liquid used for cheese storage during the production process. In addition, the ability of L. monocytogenes to grow in MBC cheese and covering liquid during shelf life, at refrigerated condition, was evaluated also this time employing microbial challenge tests. Results demonstrated that L. monocytogenes can adhere to the surface of the cheese and be released during the contact of contaminated cheese with other fluids. However, the presence of an abundant microbiota on the cheese exerted a protective role against this pathogen preventing the growth of L. monocytogenes. Indeed, the pathogens artificially contaminating the covering liquid at 2 log CFU/mL and 4 log CFU/mL remained at the inoculum level during 32 days of storage at 4 °C.

An Integral Emergency Alert System for Mexico

Mexico is a country prone to catastrophic events of seismic, vulcanological or meteorological origin, among others. For this reason, many organizations monitor in Mexico different areas to prevent catastrophes. The Emergency Alert Systems (EAS) advise about the advent of a possible catastrophic event to the population in general. This paper explores the EAS in Mexico in order to propose improvements. First, the characteristics of the existing Emergency Alert Systems in México are evaluated. As the broadcasting have traditionally been the main alert media for the population, the coverage of radio and television is studied in order to know whether it is enough to cover all the country. Finally, a new integral Emergency Alert System covering all the country is proposed.

Accident Alert System Using IoT

As technology has developed so has our methods of interacting with them. The system proposed during this paper is to detect the accident of user/person at anytime from anywhere in world. Accident threatens human lives more. Road accidents are common today. Accident Alert System (AAS) is utterly a completely unique research area. So as to avoid such collisions we’ve got designed the system called “Accident alert system using IoT”. This project presents localization system using GPS and SMS services. Many lives could have are saved if the desired attention was given at the time of need. With the assistance of this technique, the desired attention may be given to the victims by alerting the victim’s members of family, colleagues and friends. This technique helps to locate the victim and track him down. If the vehicle is stolen or misplaced then the system helps us to seek out the vehicle using GPS. The placement of the victim is transmitted to the dear ones by using GSM technology. Together with the notification as a SMS, the location at which the accident is taken place is shared using the Google maps link. Various different technologies like GSM, GPS, and switch sensor have been used for designing such system. During this report, a number of this method are discussed and revived so as to focus on their advantages, disadvantages and future scope. Accident alert system main aim is to rescuing people in accidents. Also tracking a vehicle just in case of any theft has become a tricky job. This method aims to alert the near and dear ones of the person within the vehicle about the accident to produce immediate treatment. During this system when a vehicle meets with and accident immediately impact sensor will detect the signal and send it to Arduino (atmega328p). Immediately microcontroller sends the signal to GPS module to convey the precise geographical location.

The Stoplight Mobility Alert System for Safety and Prevention of Falls in Children With Physical and Cognitive Impairments.

This study aimed to decrease the rate of falls in children with cognitive and physical impairments on a pediatric acute inpatient rehabilitation unit (IRU) using a novel tool, the Stoplight Mobility Alert System (SMAS). We conducted a pilot, prospective, quality improvement study in an 8-bed (increased to 12 beds; October 1, 2019) acute inpatient pediatric IRU at a level 1 trauma center. All patients admitted between October 1, 2012, and October 1, 2020, were included as participants. Interventions used were as follows: (1) SMAS, a colored alert system placed on door slides and in-room for visual cues (red, assistance/hands on; yellow, supervision/eyes on; green, independent/hands off), and (2) handouts and one-on-one education for staff and patients/families. Main outcome measures included fall rate on the IRU. Using the SMAS, the total fall rate decreased from 10.78 to 4.36 falls per 1000 patient-days. Longitudinally, the intrinsic fall rate decreased from 8.36 to 5.60 falls per 1000 patient-days, and the extrinsic fall rate decreased from 4.56 to 1.36 falls per 1000 patient-days. The implementation of the SMAS is effective in decreasing total, intrinsic, and extrinsic fall rates in an acute pediatric inpatient rehabilitation program both acutely and longitudinally.

Analysis of Characteristics and Quality of Life of Elderly Women with Mild to Moderate Urinary Incontinence in Community Dwellings.

Introduction: The incidence of urinary incontinence (UI) increases with age. Mild and moderate UI have little impact on women and are easily ignored. This study reports the characteristics of non-severe UI and quality of life (QOL) in elderly women using data from a Development and Evaluation of a Senile UI Alert System study. Methods: 926 women aged ≥60 were enrolled from six subcenters across China, among whom 717 SUI patients and 209 UUI/MUI patients were grouped into Group A and Group B, respectively, according to leakage symptoms. Demographic and clinical data, pelvic organ prolapse quantification and pelvic floor muscle strength measurement (PFMS) were collected from participants, followed by evaluation of QOL and sexual life. Result: The major type of UI in community women was SUI (77.4%); MUI and UUI accounted for 20.63% and 1.94%, respectively. Weakened PFMS was detected in 78.2% of the participants. Group B was significantly higher in terms of median age, weight, BMI, waist circumference and menopausal years, and had the greater UI severity and impact on QOL, as well as less active sex live than group A (p < 0.05). Conclusion: SUI distributes dominantly in elderly community women, but UUI/MUI has greater impact on QOL and is related to a less active sex life, which requires more attention from medical staff.

MO362: Braunschweig Body Composition, Butterfly Sonography and Drug Dosing in AKI Study (B3 D2 AKI––Study)

Abstract BACKGROUND AND AIMS In-hospital AKI is associated with increased morbidity and mortality. AKI Alert systems are frequently used to allow time detection of AKI patients based on changes in creatinine. We aimed to examine the hydration status, medication errors and prior existing CKD in a series of AKI 3 patients in a tertiary care hospital. METHOD Prospective single centre cohort study. Study was approved by the local IRB. Hydration status was assessed by Bioimpedance using the body composition monitor (Fresenius Medical Care). Renal size and exclusion of postrenal failure were accomplished using a point of care ultrasound system (Butterfly Network Inc.). Pharmacotherapy was entered into the Federal Medication Plan of Germany (Bundesmedikationsplan). RESULTS A total of 101 patients with AKI 3 were identified based on changes in creatinine only. The median (IQR) age was 74.0 (64.7–82.0) years with a BMI of 27.8 (23.5–34.2) kg/m2. The baseline creatinine of the patients was 1.53 (0.92–2.85) mg/dL. At the time of AKI 3 diagnosis the median [IQR] 4.1 (1.9–5.9) L. Systolic blood pressure was 116 (100–140) mmHg (Fig. 1). Median (IQR) kidney length was 10.4 (9.2–11.7) cm. Polypharmacy (&amp;gt; 5 drugs) was seen in 89.7% of all patients. Almost half of the patients (48.3%) received 10 or more drugs. A total of 38% of patients receiving an antibiotic received an inadequately high dose, followed by 7.8% receiving an inadequate dosing of oral antidiabetic drugs. CONCLUSION Patients detected by an AKI alert in a tertiary care hospital did mostly neither exhibit low blood pressure nor volume depletion. Postrenal AKI was undetected in 1 out of 101 patients. Medication dosing errors were frequently seen, especially in the dosing of antibiotics. A joined nephron-pharmacological approach seems to be important in patients with hospital acquired AKI 3.

Alert system of fisherman for secure navigation

In day-to-day life we hear news about fisherman caught and even kill by naval infantry forces of other country for crossing the international borders. The proposed system can be used by the fisherman to safeguard them with the help of Global Positioning System (GPS) module based alerting system. The system uses the GPS device to get the current location i.e., latitude and longitude values of the boat and is continuously compared with the pre-set values in controller unit. As a result of this, the system alerts by buzzer sound before five hundred meter range and when the boat is near to international borders the speed of the boat is reduced. If the shipper refused to stop the boat and continues further the system alerts the fisheries by voice alarm. At the same time the control unit stops the boat from moving further and the present location is transmitted to the coastguards with the help of RF Transceiver. This is achieved when the boat is before 200 hundred meter range to of the international borders. If the boat tries to cross the international border or the boat is taken over by other countryman naval forces, the location of the boat is transmitted to coastguard port office continuously. This system also has hijack switch and when the switch is pressed it convey the hijack information and the current location to the coastguards continuously.

Residues of veterinary drugs in fish and fish products: An analysis of RASFF data over the last 20 years

An analysis of the notifications in the European Union (EU) Rapid Alert System for Food and Feed (RASFF) portal due to residues of veterinary drugs in fish and fish products over the period 2001–2021 was conducted examining the following data: number and type of notifications; year of notification; notification basis; notifying country; country of origin; action taken; distribution status; risk decision; fish product type; residue found. A total of 292 notifications were found (mean number/year 9.8 ± 13.8 SD), mostly information notifications (60.9%). The most common notification basis was “border control - consignment detained” (38.4%), followed by “official control on the market” (37.9%) and “border control - consignment released” (13.7%). Over half (54.1%) of the notifications were issued by the United Kingdom, Germany and Spain, dominant countries in the fish processing market. Thirty-one countries of origin were recorded, but 48.6% of the notifications were referred to products from Vietnam, followed by China (15.7%), that are among the leading fish producing countries. The most common actions taken were re-dispatch (23.3%), followed by recall from consumer (10.3%), withdrawal from recipients (9.9%), destruction (9.6%), and import not authorised (9.2%). Overall, 28.8% of the notifications involved fish products belonging to the Pangasiidae family ( Pangasius spp. and Pangasianodon spp.), followed by tilapia (12.7%), trout (11.0%), eel (8.6%), catfish (7.9%) and salmon (3.4%). Triphenylmethane dyes and their metabolites were the most frequent category of residues found, accounting for 51.4% of the total notifications, followed by a wide range of antibiotics classes, of which nitrofurans and metabolites (19.5%) were the most common, while amphenicols (6.8%), quinolones and fluoroquinolones (6.5%), sulphonamides and potentiators (5.1%), tetracyclines and metabolites (3.4%) and other classes were less represented. Avermectins and unspecified residues were also found in a few cases (2.7%). The annual frequency of these issues varied and was probably influenced by dedicated monitoring plans, as well as by specific sanitary problems occurring in farms. Nevertheless, by providing historical trends and current issues, our analysis identified hazards to be closely monitored, through coordinated official controls especially in the most involved countries. • 20 years of RASFF notifications for veterinary drugs residues in fish products were analysed. • Triphenyl-methane dyes were the most frequent residue found (51.4% notifications). • Several antibiotics classes were found, mainly nitrofurans (19.5% of the notifications). • Historical and current issues to be specifically monitored were pointed out.

Facemask Detection with Alert System

Abstract: The Covid-19 is spreading across the globe. This infection spreads essentially through drops getting away from an individual contaminated with the covid, representing a threat to other people. The gamble of transmission is more noteworthy openly put. Probably the most ideal way to safeguard yourself from disease is to wear a facial mask in public regions, as expressed by the World Health Organization. In this task, we propose a strategy utilizing OpenCV and TensorFlow to recognize facial masks on a group of people. We prepared the model on various datasets so it can precisely tell regardless of whether the individual is wearing the mask. An admonition message is shown with a sound sign expressing that an individual was distinguished without a cover assuming an individual without a mask is recognized. In the wake of clicking OK, an alarm message with the depiction of the individual without a mask will be emailed and SMS. Watchwords: Opencv, Tensor stream, CNN, Smtplib, Twilio.