Types Of Alarms Research Articles

Pulse Bag Filter Fault Classifier Research and Analysis

Aiming at the problem of fault alarm flooding, a fault classifier is established to automatically classify fault types in combination with unsupervised learning methods in machine learning. The k-means method is used to classify the alarm types in dimensionality reduction, and the optimal K value is selected as 11 through various evaluation indexes, and the faults are added to the new category labels according to the center of each cluster after clustering. The random forest and support vector classification algorithm is used to establish a fault classifier model on the fault alarm dataset with new labels, and the unified analysis of the fault type prediction results of the test set unlabeled fault data set is compared with the random forest algorithm, support vector classification, and k-means method. The results show that the unity rate of the prediction results of the three types of classifiers on the test set when taking different K values can reach up to 67%, and the uniformity rate of the prediction results of the three models exceeds 0.998, which has a high degree of uniformity, indicating that the establishment of the fault alarm classifier for the pulse bag dust collector is feasible and has good classification accuracy, which can help maintenance personnel quickly locate and troubleshoot faults, and improve the intelligence level of equipment.

IoT based Fire Alerting Smart System

By combining IoT devices, such as fire alarm systems (smoke and high-temperature sensors), sensors, and other supplementary equipment, the research paper offers the "IOT based Fire Alerting Smart System" in smart buildings. The research article proposes the "IOT based Fire Alerting Smart System" in smart buildings by merging IOT devices such as fire alarm systems (smoke burn with high-temperature sensors), sensors, and other auxiliary equipment. That notification includes the time and location of fire occurs. Comparing two existing smart IoT-based fire warning systems from around the world. The Internet of Things is designed to provide organisations and individuals more visibility, and it now has the ability to govern 99 percent of available surroundings and objects that aren't connected to the Internet. Thus, IOT will be able to accomplish more meaningful work at a higher level by creating opportunities for individuals and businesses so that they can engage more with the outside world more than ever. Old fire alarm systems include many different types of devices that play a particular role in the workings of the system, detecting a person and detecting and wearing out a person through visual and auditory devices in the event of fire, smoke, monoxide carbon or others emergency. These types of alarms can be actuated by manual focus or manual fire alarms, such as suction stations, and can be activated automatically on smoke and heat detectors. The alarm can come with an electric chime. A horn or wall speaker can be a bright tone for a speaker that sounds an alarm; for example, you can add an audio evacuation message to warn you about using the elevator and other warning messages to users.

Experience of Application of GOST R 59638-2021 for the Analysis of Statistics of False Alarms of the Fire Alarm System on the Example of a Multifunctional Shopping and Entertainment Complex

Introduction. In 2021, new regulatory legal acts in the field of fire safety came into force. Special attention is paid to the control, classification and minimization of false alarms of fire protection systems and installations. In this regard, it makes sense to refer to the statistics of such triggers on specific objects in order to assess the sufficiency and validity of the criteria proposed in the new documents. The purpose of the work is to study the requirements for maintenance and operation of fire protection systems and installations. The objectives of this study are to study the main approaches to the regulation of false alarms of fire protection systems, analysis of the main quantitative indicators of the operation of systems of a particular object, assessment of the compliance of the protection object with new requirements.Materials and Methods. The empirical basis of the study was the results of constant monitoring of the state of fire protection systems and installations in one of the largest shopping and entertainment complexes in the South of Russia. The reports of the fire prevention service, data from the automated workplace of the operator of the fire station, records in operational logs were used. The information is summarized in tables by types of false alarms and by chronology. Calculations were performed in MS Excel. To identify the links between different types of false positives, a correlation analysis was carried out.Results. The connection between the number of false alarms and the intensity of work of tenants of the protection object is noted. The ratios of different types of false alarm and the significance of the triggering factors are determined. The correlation between false alarms and malfunctions of systems is revealed.Discussion and Conclusion. The methodology developed by the authors makes it possible to monitor malfunctions of fire alarm systems on an ongoing basis. A number of problematic issues of applying the classification of false alarms of the fire alarm system in GOST R 59638-2021 have been identified. A connection has been established between the number of false alarms and the intensity of the work of the tenants of the shopping center. The conclusion is made about the compliance of the protection object with the newly introduced requirements. The identified problematic issues of the application of GOST R 59638-2021 for statistical analysis in future studies force us to develop a different classification of false alarms of fire alarm systems.

Smart Home Environment Monitoring System Based on Microcontroller

More than 90% of a person’s lifetime is spent indoors in a variety of activities, thus the parameters of the home environment affect human physical and mental health. With the development of Internet of things technology, people put forward new and higher requirements for the smart home. Based on the microcontroller, in this paper, we use multiple sensor systems to monitor various indoor environmental parameters, that is, to collect and display the environmental temperature, humidity, light intensity, CO concentration, and smoke concentration accurately and in real time. In the process of monitoring, the limits of various environmental parameters can be set artificially. Different types of alarms will be activated when one or several parameters are detected to exceed the limits. The microcontroller transmits the monitoring data to mobile terminals such as smartphones and others through Bluetooth modules, and the display interface is clear and intuitive. After testing, the system has the advantages of accurate measurement results, stable performance, and simple operation, which has a certain promotion and use value in smart home environment monitoring.

An Open-Set Recognition and Few-Shot Learning Dataset for Audio Event Classification in Domestic Environments

The problem of training with a small set of positive samples is known as few-shot learning (FSL). It is widely known that traditional deep learning algorithms usually show very good performance when trained with large datasets. However, in many applications, it is not possible to obtain such a high number of samples. This paper deals with the application of FSL to the detection of specific and intentional acoustic events given by different types of sound alarms, such as door bells or fire alarms, using a limited number of samples. These sounds typically occur in domestic environments where many events corresponding to a wide variety of sound classes take place. Therefore, the detection of such alarms in a practical scenario can be considered an open-set recognition (OSR) problem. To address the lack of a dedicated public dataset for audio FSL, researchers usually make modifications on other available datasets. This paper is aimed at providing the audio recognition community with a carefully annotated dataset1 for FSL in an OSR context comprised of 1360 clips from 34 classes divided into pattern sounds and unwanted sounds. To facilitate and promote research on this area, results with state-of-the-art baseline systems based on transfer learning are also presented.

Global Emergency System Based on WPAN and LPWAN Hybrid Networks.

There are multiple methods of communication for the transmission of every type of alarm. In the case of emergency systems, they are usually controlled by private companies that work as bridges between the source and the receiver of an emergency. Furthermore, it is necessary to use an independent communication system for each building, requiring human vigilance, leading to an increase in infrastructure and service costs as well as response time. This paper proposes a hybrid network by combining both wireless personal access network (WPAN) and low power wide access network (LPWAN) communication for the complete development of a communication architecture oriented to an emergency system. The main aim of this work is to provide a global emergency system that is focused on fire detection but is also suitable for other critical events, with low energy consumption, a wide communication range covering up to 50 km, and a low cost of service and infrastructure. This proposal reduces the total energy consumption of the system with respect to typical fire detection systems.

Thoracic Impedance Pneumography-Derived Respiratory Alarms and Associated Patient Characteristics.

Respiratory rate (RR) alarms alert clinicians to a change in a patient's condition. However, RR alarms are common occurrences. To date, no study has examined RR alarm types and associated patient characteristics, which could guide alarm management strategies. To characterize RR alarms by type, frequency, duration, and associated patient demographic and clinical characteristics. A secondary data analysis of alarms generated with impedance pneumography in 461 adult patients admitted to either a cardiac, a medical/surgical, or a neurological intensive care unit (ICU). The RR alarms included high parameter limit (≥30 breaths/min), low parameter limit (≤5 breaths/min), and apnea (no breathing ≥20 s). The ICU type; total time monitored; and alarm type, frequency, and duration were evaluated. Of 159 771 RR alarms, parameter limit alarms (n = 140 975; 88.2%) were more frequent than apnea alarms (n = 18 796; 11.8%). High parameter limit alarms were most frequent (n = 131 827; 82.5%). After ICU monitoring time was controlled for, multivariate analysis showed that alarm rates were higher in patients in the cardiac and neurological ICUs (P = .001), patients undergoing mechanical ventilation (P = .005), and patients without a ventricular assist device or pacemaker (P = .02). Male sex was associated with low parameter limit (P = .01) and apnea (P = .005) alarms. High parameter limit RR alarms were most frequent. Factors associated with RR alarms included monitoring time, ICU type, male sex, and mechanical ventilation. Although these factors are not modifiable, these data could be used to guide management strategies.

Comparative study of the cost of implementing wireless technologies for IoT and M2M for the last mile: A case study

The need to determine which wireless IoT technology, currently available on the market, will be able to support a sizeable simultaneous load of information, types of electrical emergency alarms, required bandwidths, delays-latency, area coverage, and economic cost to serve areas of 600 square kilometers of surface and several users of around two million homes. This article compares Sigfox, LoRa, NB-IoT, and WiMAX technologies as possible solutions for last-mile communications. For this purpose, a network of hundreds of smart meters has been simulated, each transmitting different types of information. In conclusion, it has been obtained that, for a context with the priority of alarms and a large amount of information transport in massive last-mile communications in smart grids and for electrical metering traffic, it is highly recommended that it be done through WiMAX, which in the evaluation shows the best result compared to the other technologies.

SOMN_IA: Portable and Universal Device for Real-Time Detection of Driver’s Drowsiness and Distraction Levels

In this paper, we propose a portable device named SOMN_IA, to detect drowsiness and distraction in drivers. The SOMN_IA can be installed inside of any type of vehicle, and it operates in real time, alerting the dangerous state caused by drowsiness and/or distraction in the driver. The SOMN_IA contains three types of alarm: light alarm, sound alarm, and the transmission of information about the driver’s dangerous state to a third party if the driver does not correct his/her dangerous state. The SOMN_IA contains a face detector and a classifier based on the convolutional neural networks (CNN), and it aids in the management of consecutive information, including isolated error correction mechanisms. All of the algorithmic parts of the SOMN_IA are analyzed and adjusted to operate in real-time in a portable device with limited computational power and memory space. The SOMN_IA requires only a buck-type converter to connect to the car battery. The SONM_IA discriminates correctly between real drowsiness and normal blinking, as well as between real dangerous distraction and a driver’s normal attention to his/her right and left. Although the real performance of the SOMN_IA is superior to the CNN classification accuracy thanks to isolated error correction, we compare the CNN classification accuracy with the previous systems.

Computational approaches to alleviate alarm fatigue in intensive care medicine: A systematic literature review.

Patient monitoring technology has been used to guide therapy and alert staff when a vital sign leaves a predefined range in the intensive care unit (ICU) for decades. However, large amounts of technically false or clinically irrelevant alarms provoke alarm fatigue in staff leading to desensitisation towards critical alarms. With this systematic review, we are following the Preferred Reporting Items for Systematic Reviews (PRISMA) checklist in order to summarise scientific efforts that aimed to develop IT systems to reduce alarm fatigue in ICUs. 69 peer-reviewed publications were included. The majority of publications targeted the avoidance of technically false alarms, while the remainder focused on prediction of patient deterioration or alarm presentation. The investigated alarm types were mostly associated with heart rate or arrhythmia, followed by arterial blood pressure, oxygen saturation, and respiratory rate. Most publications focused on the development of software solutions, some on wearables, smartphones, or headmounted displays for delivering alarms to staff. The most commonly used statistical models were tree-based. In conclusion, we found strong evidence that alarm fatigue can be alleviated by IT-based solutions. However, future efforts should focus more on the avoidance of clinically non-actionable alarms which could be accelerated by improving the data availability.Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021233461, identifier: CRD42021233461.

Analyzing the influence of the fire resistance of building structures on human safety in case of a fire

Introduction. Methodological provisions must be developed to evaluate the impact of the fire resistance factor of building structures on human safety during evacuation and rescue with account taken of the composition andfunctional characteristics of other fire safety systems to formulate modern regulatory requirements for the fire resistance of building structures under fire conditions, develop science-based solutions for the fire safety of buildings and structures in case of forced deviations from the fire resistance requirements set in regulatory documents, and justify the construction of buildings and structures, based on modern structural systems, having non-standard fire resistance limits, etc.The purpose of the article is to develop general methodological provisions and mathematical relationships that allow evaluating the impact of the fire resistance limits of building structures both on safe evacuation and safe rescue from buildings.Methods. Analytical and mathematical methods are used to evaluate the combined effect of changes in the fire hazard arising along the evacuation routes, in a room with a person waiting to be rescued by fire departments, as well as along the routes taken by fire departments carrying this person out, in combination with the evaluated time span needed for the structure to lose its fire resistance. The value of this time span is used to identify the time available for the safe evacuation and rescue of people.Results. Theoretical provisions have been developed to take into account the influence of the fire resistance factor of building constructions on the safety of people in a building in case of a fire.Conclusions. The research findings were contributed to the general methodological provisions and mathematical relationships needed to determine the quantitative relationships between the extent of fire resistance of a building, fire resistance limits of building structures, the time of arrival of fire departments, types of fire alarm and evacuation control systems, and the possibility of safe evacuation and rescue of people from a building.

Vocal recognition of alarm calls in wild putty-nosed monkeys, Cercopithecus nictitans

Vocal recognition in social contexts is phylogenetically widespread and can be explained by kin and mate recognition or group coordination. It remains unclear why some species evolved alarm calls that also provide cues to signaller identity as the function of these calls is thought to predominantly serve predation avoidance. One hypothesis is that individually distinct alarms facilitate the detection of unreliable callers, which is in line with the idea of reputation-based mate choice. However, it remains unknown whether receivers use provided cues to identify the signaller and, if yes, how vocal signaller recognition impacts on their own behaviour during predation events. In many nonhuman primates, males provide risky antipredator services to the rest of the group while uttering conspicuous alarm calls. In putty-nosed monkeys, some male alarm types have been shown to be individually distinct and females have been shown to vocally recruit males for predation defence. Whether females are sensitive to the identity of the male supporting them in predation defence is unknown. We tested 16 groups of putty-nosed monkeys in the Nouabalé Ndoki National Park (Republic of Congo) with different alarm types from different males. Specifically, we broadcast pyow, hack and kek calls from the group's own male, a neighbouring male and an unknown male, respectively, to each group. Female receivers were sensitive to signaller identity and consistently varied their own antipredator behaviour between different males for two call types but not for eagle-related hacks. We explored different possible explanations for male recognition based on risky male antipredator services and conclude that our results are strongly in line with the reputation-based mate choice hypothesis.

Pengaruh Jenis Kemasan Terhadap Karakteristik Cookies Ampas Tahu Selama Penyimpanan


 
 
 This study aims to determine the effect of the type of packaging on tofu dregs cookies during storage and the best type of packaging alarm that can maintain the balance of tofu dregs cookies during storage. The experimental design used was factorial Completely Randomized Design (CRD) with 2 factors. The first factor was the type of packaging with 3 levels, namely K1 = Polypropylene, K2 = Polyethylene, K3 = Aluminum Foil. The second factor, namely storage time with 5 stages, namely P0 = 0 weeks, P1 = 1 week, P2 = 2 weeks, P3 = 3 weeks, and P4 = 4 weeks. The treatment was repeated 2 times in order to obtain 30 experimental units. The data obtained were analyzed using Analysis of Variance (ANOVA). If the influence affects the test parameters, then test with Duncan's Multiple Range Test. The type of packaging during storage affects water content, texture, crude fiber content, TBA number, hedonic test (aroma, texture, color, taste and overall acceptance). This type of aluminum foil packaging can maintain the characteristics of tofu dregs cookies for up to 3 weeks with the following characteristics: moisture content of 3.73%, texture 51.90 N, crude fiber content 4.20%, TBA number 0.32 mg malonaldehyde / kg, for preference tests such as color, aroma, texture, taste and overall acceptance is preferred.
 
 

Premature ventricular complexes during continuous electrocardiographic monitoring in the intensive care unit: Occurrence rates and associated patient characteristics.

This study examined the occurrence rate of specific types of premature ventricular complex (PVC) alarms and whether patient demographic and/or clinical characteristics were associated with PVC occurrences. Because PVCs can signal myocardial irritability, in-hospital electrocardiographic (ECG) monitors are typically configured to alert nurses when they occur. However, PVC alarms are common and can contribute to alarm fatigue. A better understanding of occurrences of PVCs could help guide alarm management strategies. A secondary quantitative analysis from an alarm study. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist was followed. Seven PVC alarm types (vendor-specific) were described, and included isolated, couplet, bigeminy, trigeminy, run PVC (i.e. VT >2), R-on-T and PVCs/min. Negative binomial and hurdle regression analyses were computed to examine the association of patient demographic and clinical characteristics with each PVC type. A total of 797,072 PVC alarms (45,271 monitoring hours) occurred in 446 patients, including six who had disproportionately high PVC alarm counts (40% of the total alarms). Isolated PVCs were the most frequent type (81.13%) while R-on-T were the least common (0.29%). Significant predictors associated with higher alarms rates: older age (isolated PVCs, bigeminy and couplets); male sex and presence of PVCs on the 12-lead ECG (isolated PVCs). Hyperkalaemia at ICU admission was associated with a lower R-on-T type PVCs. Only a few distinct demographic and clinical characteristics were associated with the occurrence rate of PVC alarms. Further research is warranted to examine whether PVCs were associated with adverse outcomes, which could guide alarm management strategies to reduce unnecessary PVC alarms. Targeted alarm strategies, such as turning off certain PVC-type alarms and evaluating alarm trends in the first 24 h of admission in select patients, might add to the current practice of alarm management.

Design of serial alarm systems based on deadbands and delay timers for removing false alarms

Alarm deadbands and delay timers are widely used in practice to remove false alarms. This paper proposes a method to design serial alarm systems that are composed of alarm deadbands serially followed by delay timers. Serial alarm systems are effective for removing false alarms with different types of alarm deviations and alarm durations, while alarm deadbands or delay timers alone are suitable only for one type of false alarms. A minimization problem is formulated to simultaneously design optimal values of the alarm deadband width and delay timer factor, for achieving a desired ratio of false alarms to be remove. Bayesian estimation approach is exploited to resolve a main technical challenge in achieving reliable estimates of joint probabilities of alarm deviations and alarm durations. Existing methods are confined to the isolated design of alarm deadbands or delay timers based on probability density functions of process variables, and are subject to a restrictive assumption that process variables are independent and identically distributed. By contrast, the proposed method is for the joint design of serially-connected alarm deadbands and delay timers; it is based on joint probabilities of alarm deviations and alarm durations, and does not require the restrictive assumption. Numerical and industrial examples are provided to illustrate the proposed method and compare with existing ones.

The Duration of an Auditory Icon Can Affect How the Listener Interprets Its Meaning

Initially introduced in the field of informatics, an auditory icon consists of a short sound that is present in everyday life, used to represent a specific event, object, function, or action. Auditory icons have been studied in various fields, and overall, compared to other types of auditory alarms, they can be very efficient in informing the listener about a situation or event. So far, auditory icons have been used with a wide range of durations, ranging from a few hundreds of milliseconds up to several seconds. Still little is known, however, about whether and how icon duration influences its interpretation. In the present study, we therefore asked listeners to rate 12 auditory icons, divided into four different sound categories (nonverbal human sounds, machine sounds, human activities, and animal vocalizations), in five different durations (200, 400, 800, 1,600, and 3,200 ms). They rated (1) how appropriately the icon sound itself represented the icon's referent and (2) how appropriately each duration of the icon sound represented the icon's referent. Overall, results demonstrate that the duration of the auditory icons in this stimulus set can directly affect how the icon represents the referent. Auditory icons in the test set characterized by human activities represented their referent most appropriately in a relatively shorter duration (400 or 800 ms). The majority of the auditory icons in the set consisting of machine sounds, nonverbal human sounds , and animal vocalizations , however, were considered as more appropriately representing their referent in longer durations (800 ms and 1,600 ms). Further systematic research is necessary to determine whether the duration effects shown here may generalize to other stimulus sets.

Age-Dependent Responsiveness to Smoke Alarm Signals Among Children.

Although it has been established that smoke alarms have more difficulty awakening children from sleep than adults, no attempt has been previously made to characterize how smoke alarm responsiveness changes with age during childhood. The objective of this study is to evaluate the age-dependent responsiveness to various smoke alarm signals among children 5 to 12 years old. The effect of age on children's response to 4 types of smoke alarms (human voice, hybrid voice-tone, low-frequency tone, and high-frequency tone) was evaluated using combined data from 3 previous studies. There were 540 subjects (median age 9 years; 51.7% male). The proportion of children who awakened demonstrated a statistically significant (P < .001) increase of 3.1% to 7.6% for each additional year of age between 5 and 12 years old for the 4 alarm types. Similarly, child age showed a statistically significant (P < .001) effect on the proportion who escaped for each of the 4 alarm types. The proportion of subjects who awakened or escaped did not differ significantly by sex for any of the alarm types. Median time-to-awaken and median time-to-escape decreased with increase in child age for all alarm types. This study demonstrates the substantial influence of child age on the effectiveness of audible smoke alarms during childhood. Among 12-year-olds, only 56.3% escaped within 1 minute (and 67.6% within 2 minutes) to a high-frequency tone. However, a hybrid voice-low-frequency tone alarm is >96% effective at awakening and prompting escape within 1 minute among children 9 years and older.

A contrastive learning approach for\xa0ICU false arrhythmia\xa0alarm reduction

The high rate of false arrhythmia alarms in Intensive Care Units (ICUs) can lead to disruption of care, negatively impacting patients’ health through noise disturbances, and slow staff response time due to alarm fatigue. Prior false-alarm reduction approaches are often rule-based and require hand-crafted features from physiological waveforms as inputs to machine learning classifiers. Despite considerable prior efforts to address the problem, false alarms are a continuing problem in the ICUs. In this work, we present a deep learning framework to automatically learn feature representations of physiological waveforms using convolutional neural networks (CNNs) to discriminate between true vs. false arrhythmia alarms. We use Contrastive Learning to simultaneously minimize a binary cross entropy classification loss and a proposed similarity loss from pair-wise comparisons of waveform segments over time as a discriminative constraint. Furthermore, we augment our deep models with learned embeddings from a rule-based method to leverage prior domain knowledge for each alarm type. We evaluate our method using the dataset from the 2015 PhysioNet Computing in Cardiology Challenge. Ablation analysis demonstrates that Contrastive Learning significantly improves the performance of a combined deep learning and rule-based-embedding approach. Our results indicate that the final proposed deep learning framework achieves superior performance in comparison to the winning entries of the Challenge.

Improved Patient Monitoring with a Novel Multisensory Smartwatch Application.

The design of medical alarms has been heavily criticized in the past decade. Auditory medical alarms have poor learnability, discernibility, and relevance, leading to poor patient outcomes, and alarm fatigue, and overall poor informatic system design. We developed a novel trimodal patient monitoring smartwatch application for patient monitoring. Participants completed two phases: (1) control and (2) our novel trimodal system while identifying alarms (heart rate, oxygenation, and blood pressure) and completing a cognitively demanding task. Alarms were auditory icons presented as either solo or co-alarms. Participant performance was assessed by accuracy and response time (RT) of alarm identification. Using the novel system, accuracy was significantly improved overall (p < 0.01) and in co-alarm situations (p < 0.01), but not for solo alarms (p = 0.484). RT was also significantly faster (p < 0.01) while using the novel system for all alarm types. Participants reported decreased mental workload using the novel system. This feasibility study shows that our novel alarm system performs better than current standards. Improvements in accuracy, RT and perceived mental workload indicate the potential of this system to have a positive impact on medical informatic systems and clinical monitoring, for both the patient and the clinician.

Parent-offspring and inter-offspring responses to conspecific versus heterospecific distress calls in 2 sympatric birds.

Distress calls, as a type of alarm call, play important roles in expressing bodily condition and conveying information concerning predation threats. In this study, we examined the communication via distress calls in parent-offspring and inter-offspring interactions. First, we used playback of chick distress calls of 2 sympatric breeders, the vinous-throated parrotbill Sinosuthora webbiana and the oriental reed warbler Acrocephalus orientalis, to the adults/chicks of these 2 species, respectively, and measured the responses of conspecifics or heterospecifics. The playback-to-chicks experiment showed that both species of chicks reduced the number of begging calls and begging duration time as a response to conspecific/heterospecific distress calls compared with natural begging and background noise controls. However, reed warbler chicks also reduced beak opening frequency in the response to conspecific distress calls compared with other playback stimuli. Second, the results of the playback-to-adults experiment showed that reed warbler adults could eavesdrop on distress calls of conspecific neighbors and sympatric heterospecifics. Furthermore, the nest-leaving behavior of reed warblers did not differ significantly when they heard the distress calls of conspecifics or parrotbills. Finally, reed warbler adults responded to heterospecific distress calls more quickly than to conspecific distress calls, and parrotbill adults presented the same response. Our results supported the warn-kin hypothesis and show that chick distress calls play an important role in conveying risk and the condition of chicks to enhance individual fitness. In addition, we also found that eavesdropping on distress calls is a congenital behavior that begins in the chick stage.