Instant Alerts Research Articles

GSM Based Transformer Healthcare Monitoring with Overload Alert and Protection

The "Transformer Health Monitoring System" project presents a proactive and cost-effective solution for monitoring power transformers in electrical distribution networks, addressing the critical need for reliable maintenance. Leveraging the ATmega328P microcontroller, the system continuously monitors vital parameters such as oil level, quality, voltage, current, and temperature. With real-time data visualization through a user-friendly display module and advanced fault detection algorithms, the system ensures prompt identification of issues. Integration of a GSM module enables instant alerts to designated recipients, facilitating swift response to faults. Scalability across multiple transformers streamlines monitoring and maintenance, enhancing grid stability, reducing downtime, and supporting environmental conservation efforts. This project underscores a commitment to reliability, safety, and sustainability in power distribution networks..

Human Detection for the Betterment of Security System Using PIR Sensor and BLYNK App

Abstract: The Human Detection System (HDS) presented in this project utilizes Passive Infrared (PIR) sensors, Node MCU microcontroller, and the Blynk IoT app to detect human presence in a designated area, providing real-time monitoring and instant alerts. Additionally, an ESP32 module camera is integrated into the system to visually confirm detected events. Upon sensor activation, the ESP32 camera captures footage of the area, allowing users to verify the validity of the alert via a provided link accessible on mobile or laptop devices. This comprehensive approach enhances security measures by combining both sensor-based detection and visual confirmation capabilities, offering an effective solution for surveillance applications.

Intelligent Travel Companion: The IoT-Enabled Smart Bag

The Smart IoT Bag represents a revolutionary integration of technology into everyday accessories, transforming a conventional item into an intelligent and connected device. This innovative bag incorporates a range of Internet of Things (IoT) features that enhance user experience, convenience, and security. At its core, the Smart IoT Bag is equipped with embedded sensors and connectivity modules, enabling it to gather real-time data about its surroundings and the items it contains. One key aspect of the Smart IoT Bag is its ability to provide users with smart inventory management. Through RFID or NFC technology, the bag can track the presence and location of specific items placed within it. This feature proves invaluable for individuals who frequently misplace their belongings, offering a seamless and efficient way to locate items through a dedicated mobile application. Furthermore, the Smart IoT Bag embraces the concept of smart security. Integrated with biometric authentication, the bag ensures that only authorized users can access its contents. In the event of theft or unauthorized access, the bag can send instant alerts to the user's smartphone, allowing for swift action. Additionally, the bag is equipped with GPS tracking, enabling users to pinpoint its location in real-time, enhancing security and providing peace of mind. The bag's connectivity extends beyond personal use, contributing to a broader ecosystem of interconnected devices. It can seamlessly integrate with smart home systems, allowing users to automate tasks based on the bag's status or location. For instance, upon arriving home, the bag could trigger the lights to turn on or adjust the thermostat.

A Robust and Automated Vision-Based Human Fall Detection System Using 3D Multi-Stream CNNs with an Image Fusion Technique

Unintentional human falls, particularly in older adults, can result in severe injuries and death, and negatively impact quality of life. The World Health Organization (WHO) states that falls are a significant public health issue and the primary cause of injury-related fatalities worldwide. Injuries resulting from falls, such as broken bones, trauma, and internal injuries, can have severe consequences and can lead to a loss of mobility and independence. To address this problem, there have been suggestions to develop strategies to reduce the frequency of falls, in order to decrease healthcare costs and productivity loss. Vision-based fall detection approaches have proven their effectiveness in addressing falls on time, which can help to reduce fall injuries. This paper introduces an automated vision-based system for detecting falls and issuing instant alerts upon detection. The proposed system processes live footage from a monitoring surveillance camera by utilizing a fine-tuned human segmentation model and image fusion technique as pre-processing and classifying a set of live footage with a 3D multi-stream CNN model (4S-3DCNN). The system alerts when the sequence of the Falling of the monitored human, followed by having Fallen, takes place. The effectiveness of the system was assessed using the publicly available Le2i dataset. System validation revealed an impressive result, achieving an accuracy of 99.44%, sensitivity of 99.12%, specificity of 99.12%, and precision of 99.59%. Based on the reported results, the presented system can be a valuable tool for detecting human falls, preventing fall injury complications, and reducing healthcare and productivity loss costs.

Design of A Security System with Mobile Notifications in Case of Intrusion

Physical security is a crucial aspect of cybersecurity, considering the constant risk of unauthorized intrusions and data theft that companies face. While conventional security measures like alarm systems and video surveillance aim to protect physical infrastructure, they often fall short of meeting businesses' actual requirements. It is vital for companies to have immediate awareness of intrusions and the ability to respond promptly. To tackle this challenge, the recommended approach involves implementing an alert security system that offers real-time notifications. This method entails deploying an Internet of Things (IoT) system equipped with sensors throughout the company's premises. These sensors are specifically designed to detect unauthorized entry, triggering instant alerts to the appropriate personnel via a dedicated mobile application. This application enables seamless communication with the IoT system, enabling swift decision-making in response to potential security breaches. In this research, the initial emphasis was on designing the system using Unified Modeling Language (UML) diagrams. Subsequently, the IoT system was implemented, integrating the necessary sensors. Additionally, a user-friendly application was developed to establish a secure connection between the company's system and employees' mobile devices. Through extensive research efforts, an effective and functional system capable of effectively safeguarding businesses has been successfully devised.

Proactive Headcount and Suspicious Activity Detection using YOLOv8

Global population growth has resulted in more public gatherings, raising concerns on overcrowding and associated safety problems. Among these safety issues, crowd-smashing accidents stand out as unexpected and fast growing situations that pose serious risks to common people. Manually predicting and managing such chaotic situations leads to various challenges. To address these challenges, AI-based monitoring systems are currently used by integrating cutting-edge object detection algorithms such as YOLOv8. This advanced approach provides authorities with real-time crowd density evaluations and instant alerts, enabling immediate action and accident avoidance. Notably, the proposed model extends its capabilities beyond crowd counting by encompassing the detection of abnormal activities such as weapons, fires, falls, and smoke within the crowd. By identifying potentially dangerous crowd densities and quickly detecting abnormal incidents, the proposed system not only prevents disasters such as crowd smashing but also strengthens security measures, putting public safety at the forefront of the challenges posed by a growing global population and crowded public spaces.

Analysis of the Challenges of Artificial Intelligence of Things (AIoT) for the Smart Supply Chain (Case Study: FMCG Industries).

In today’s competitive world, supply chain management is one of the fundamental issues facing businesses that affects all an organization’s activities to produce products and provide services needed by customers. The technological revolution in supply chain logistics is experiencing a significant wave of new innovations and challenges. Despite the current fast digital technologies, customers expect the ordering and delivery process to be faster, and as a result, this has made it easier and more efficient for organizations looking to implement new technologies. “Artificial Intelligence of Things (AIoT)”, which means using the Internet of Things to perform intelligent tasks with the help of artificial intelligence integration, is one of these expected innovations that can turn a complex supply chain into an integrated process. AIoT innovations such as data sensors and RFID (radio detection technology), with the power of artificial intelligence analysis, provide information to implement features such as tracking and instant alerts to improve decision making. Such data can become vital information to help improve operations and tasks. However, the same evolving technology with the presence of the Internet and the huge amount of data can pose many challenges for the supply chain and the factors involved. In this study, by conducting a literature review and interviewing experts active in FMCG industries as an available case study, the most important challenges facing the AIoT-powered supply chain were extracted. By examining these challenges using nonlinear quantitative analysis, the importance of these challenges was examined and their causal relationships were identified. The results showed that cybersecurity and a lack of proper infrastructure are the most important challenges facing the AIoT-based supply chain.

An Alternative Body Temperature Measurement Solution: Combination of a Highly Accurate Monitoring System and a Visualized Public Health Cloud Platform.

To quickly isolate suspected cases to control the epidemics, this study proposes a body temperature monitoring system with a thermography based on the Internet of Things (IoT) architecture. The collected data are transmitted to a back-end platform via wireless communication. Using the analyzed data, the platform provides services, such as instant alerts for any anomalies, infectious disease outbreak prediction, and risk level assessment for a given area, and it will be a great help to epidemic prevention. The mean absolute percentage error and root mean square error of the proposed monitoring system under an extensive series of experiments are 0.04% and 0.0204°C, respectively. It shows that the body temperature measured by the thermal imaging sensor in the system can accurately represent the actual body temperature after specific calibrations that take the environmental temperature into account. It can also be expanded to a decision supporting system to help schools or government agencies to make proper decisions to stop the spread of infectious diseases.

Harnessing Teams and Technology to Improve Outcomes in Infants With Single Ventricle

Infants with single ventricle require staged cardiac surgery, with stage I typically performed shortly after birth, stage II at 4 to 6 months of age, and stage III at 3 to 5 years of age. There is a high risk of interstage mortality and morbidity after infants are discharged from the hospital between stages I and II. Traditional home monitoring requires caregivers to record measurements of weight and oxygen saturation into a binder and requires families to assume a surveillance role. We have developed a tablet PC-based solution that provides secure and nearly instantaneous transfer of patient information to a cloud-based server, with the capacity for instant alerts to be sent to the caregiver team. The cloud-based IT infrastructure lends itself well to being able to be scaled to multiple sites while maintaining strict control over the privacy of each site. All transmitted data are transferred to the electronic medical record daily. The system conforms to recently released Food and Drug Administration regulation that pertains to mobile health technologies and devices. Since this platform was developed in March 2014, 30 patients have been monitored. There have been no interstage deaths. The experience of care providers has been unanimously positive. The addition of video has added to the use of the monitoring program. Of 30 families, 23 expressed a preference for the tablet PC over the notebook, 3 had no preference, and 4 preferred the notebook to the tablet PC.

Abstract 16644: Interstage Clinical Outcomes and Resource Utilization Among Babies With Single Ventricle: Results of A Randomized Cross-over Study Comparing Standard of Care (Notebook) to Tablet PC-Based Monitoring

Interstage outcomes for babies with single ventricle remain suboptimal. We have developed a tablet PC-based platform (CHAMP) for remote monitoring. This provides immediate access to data and instant alerts to the team. This study evaluates the caregiver experience with CHAMP, and its impact on interstage mortality, morbidity and resource utilization. Methods: All neonates with single ventricle who were discharged from 5/2014 to 5/2015 were prospectively enrolled. For 1 month after discharge, they were all monitored using a notebook. They were randomized to receive CHAMP at either 1 or 2 months post discharge. A month after randomization, caregivers had to choose either the notebook or CHAMP for the remainder of the inter-stage period. Charts were reviewed for mortality, unplanned readmissions and hospital charges. Caregiver experience was assessed through an exit survey. Results: We enrolled 24 babies (Norwood, n=11; BT shunt, n=9; no stage I at discharge (balanced circulation), n=3; hybrid, n=1). They were interstage for 3143 days. There was no interstage mortality in either group. While using CHAMP, families transmitted data on 77% of days. Resource utilization is summarized in the Table. CHAMP instant alerts and scheduled daily alerts led to 10 readmissions for issues that were not recognized by caregivers (low saturations (n=6) and poor feeding / weight gain (n=4). When given the option after randomization, 23 of 24 families chose CHAMP. At the end of monitoring, 23 completed an exit survey; when asked what form of monitoring they would choose if they had to do this over, 19 (82%) stated they would choose CHAMP, 3 would choose either, and 1 would choose the notebook. Conclusions: CHAMP monitoring was associated with significant decreases in unplanned readmission days, ICU days and hospital charges. CHAMP was well-accepted by caregivers, and would appear to facilitate outpatient care for the fragile population of interstage babies with single ventricle.

(P2-15) Problems of Permanent Threat of Impact on Persons Authorized as Drivers

IntroductionPeople using public transportation have to put their health and even their lives in the hands of personnel authorized to drive the vehicles. But, organizers are taking unprecedented measures to protect transportation from diverse threats. However, there is often overwhelming evidence of the weak effectiveness of pertinent measures.MethodThere is a permanent threat of possible physical and/or psychological impact on persons authorized as drivers, which leads to a possible threat to the health and lives of others. Such events can be divided into two groups: (1) pre-driving; and (2) in-driving. Anthropogenic impacts while pre-driving and in-driving periods stimulate feelings of fear, which comprises different components.ResultsIn the pre-driving group, drivers face overwhelming mental health impacts. This includes fear for their lives and health, fear of responsibility for family, friends, and passengers. In the in-driving group, the variation of physical and mental impacts determines the addition of fears of other categories.ConclusionIntegrated sensors for measuring levels of blood pressure, sweating, heart rate, respiratory rate, and changes in the retina of the eye should be implemented. This hardware and software should process information about drivers. They would provide instant alerts on changes in the indicators.

An Investigation of an RFID-based Patient-Tracking and Mobile Alert System

In the modern era, patient health is no longer the only concern for hospitals. Hospitals have to bear the responsibility of the patient safety and the patient comfort. However, due to the overcrowded and understaffed clinical areas with complex workflow patterns, there are different forms of medical care errors arisen in the healthcare system. According to recent statistic from World Health Organization, ten of milions of patient around the world are injured or dead every yearas a result of incorrect medical care. Rroughly 10% patients admitted to hospital in developed countries suffered some forms of medical care errors or medical adverse events. It is about 1.4 million of world population. In order to enhance the patient safety and patient comfort in the current medical service system, an RFID-based Patient Tracking and Mobile Alert System integrated with information communications technology was designed and developed. Apart from identifying different patient's whereabouts, instant alerts are generated through mobile devices so as to enhance patients' safety and comfort. With a view of investigating the feasibility of RFID and mobile technology in the healthcare environment, a pilot study was conducted in Mindset Club in the Castle Peak Hospital in Hong Kong.

Psychotherapist self-disclosure and transparency in the Internet age.

Summary and Recommendations Self-disclosure is a broad term that includes psychotherapists’verbal and nonverbal, intentional and unintentional, avoidable andunavoidable disclosures about themselves and their lives. Themeaning of self-disclosure can commonly be understood onlywithin the context of psychotherapy, which includes client, setting,type of psychotherapy, and psychotherapist factors. Self-disclosures that are clinically appropriate in one context may notbe in another. Some treatment plans may call for extensive self-disclosure while others may call for minimal self-disclosure. In-tentional self-disclosures must be constructed to enhance the treat-mentplanandmustfirstandforemostbeconsiderateoftheclient’swelfare.Clinicians must ensure that the self-disclosures are not done tofulfill their needs but rather those of the clients. Clinically drivenself-disclosure that is done for the welfare of the client can be verybeneficial for treatment and can enhance therapeutic alliance,the best predictor of therapeutic outcome. Any form of extensiveself-disclosure, whether intentional or unintentional, shouldbe documented and its clinical meaning should be discussed in theclinical records.Our modern “bare it all” culture and the fact that many mentalhealth clients view themselves as informed consumers rather than“patients” have created an expectation of caregivers’ transparency.Digital technologies have significantly increased psychotherapisttransparency and have drastically changed the playing field. Cli-nicians must be aware that all their online postings, blogs, or chatsmay be viewed by their clients and will stay online, in some form,forever. They should search themselves online periodically bysimply putting their names, in different combinations (i.e., Dr.Smith, Smith, PhD, or Jane Smith), into a Google search. Anothereasy way to keep track of one’s online presence is by signing upfor “Google Alerts” (at http://www.google.com/alerts?hl en) inorder to get instant alerts when one’s name is mentioned in a newposting. When clients intrude into clinicians’ personal lives, clini-cians should consider the clinical, ethical, and legal implicationsand, if necessary, consult with their professional association, ex-perts in the field, and a knowledgeable attorney, if necessary.Removing inaccurate, negative or slanderous material from theInternet can be very challenging and may require professional orlegal assistance.The effect of the Internet on self-disclosure and clinical practicehas yet to be fully understood and thoroughly studied. The threeinvited expert commentaries to follow address these and relatedchallenges, issues, and dilemmas that psychologists face regardingself-disclosure, in general, and specifically in the Internet age.