Effects of Vibration Sensor on Mitigation Risk of Halal Chicken Slaughtering System

To cite this paper: Rosyidi K, Santoso I, Wibisono Y, and Sucipto S. (2025). Effects of Vibration Sensor on Mitigation Risk of Halal Chicken Slaughtering System. J. World Poult. Res., 15(3): 338-349. DOI: https://dx.doi.org/10.36380/jwpr.2025.33 338 JWPR Journal of World’s Poultry Research 2025, Scienceline Publication J. World Poult. Res. 15(3): 338-349, 2025 Research Paper DOI: https://dx.doi.org/10.36380/jwpr.2025.33 PII: S2322455X2400033-15 Effects of Vibration Sensor on Mitigation Risk of Halal Chicken Slaughtering System Khafizh Rosyidi1* , Imam Santoso1 , Yusuf Wibisono2 , and Sucipto Sucipto1,3 1Department of Agroindustrial Technology, Brawijaya University, Malang, Indonesia 2Department of Biosystem Engineering, Brawijaya University, Malang, Indonesia 3 Center for Halal Ecosystem Development (HED), Brawijaya University, Malang, Indonesia *Corresponding author’s E-mail: [email protected] Received: July 10, 2025, Revised: August 14, 2025, Accepted: September 11, 2025, Published: September 30, 2025 ABSTRACT Ensuring compliance with halal standards in poultry slaughtering involves both following religious principles and implementing strict scientific and technological measures. Integrating Internet of Things (IoT) technology provides opportunities to enhance the reliability and objectivity of halal verification processes, particularly in identifying critical control points, such as animal death, specifically the death of chickens during the slaughter process, before entering the scalding stage. The present study aimed to design a halal risk mitigation system based on IoT, focusing on the critical point of complete chicken death, defined as the total absence of movement in the chicken after slaughter, through critical analysis. It is known that the stage between postslaughter and pre-burning is the most crucial phase, where the highest risk is that the chicken has not entirely died due to ineffective slaughter. This system was developed using a NodeMCU ESP8266 microcontroller connected to a vibration sensor or passive infrared sensor and was equipped with real-time notifications via the Thingspeak cloud dashboard, indicating the waiting time for complete death and the number of vibrations. Testing on 30 chickens demonstrated a detection accuracy of 92.5% compared to manual observations by halal auditors, with consistent performance across different environmental conditions. This system can detect the movement of chicken remains after slaughter in an average of 15 to 20 seconds, providing an early warning of potential halal violations rules. The current results demonstrated that the vibration sensor effectively facilitated the execution of halal slaughtering principles through an early-warning mechanism designed to prevent chickens from entering the scalding phase while still alive. This ensures the humane death of chickens and the regulation of halal critical control points in line with the Indonesian national standard for halal poultry slaughter. Keywords: Criticality analysis, Halal slaughter, Risk management, Poultry industry, Vibration sensor INTRODUCTION The global demand for halal products continues to grow significantly worldwide. This increase is driven not only by the growing Muslim population but also by consumers from different backgrounds who are increasingly valuing food integrity, safety, and quality (Herdiana et al., 2024). In Indonesia, which has the largest Muslim population, halal certification for animal food products goes beyond a religious obligation; it has also become an ethical and regulatory standard within the national food system (Pradana et al., 2024). As a result, the halal aspect has become a primary focus in supervising and managing the food supply chain, particularly in processes directly related to sharia requirements, such as slaughtering in slaughterhouses. One of the most crucial issues in the halal poultry slaughter process is to ensure that each chicken experiences complete death as a direct result of slaughter, defined as the complete absence of movement in the chicken after slaughter (Nielsen et al., 2019). This complete death is one of the main requirements for the validity of slaughter according to Islamic law (Jelan et al., 2024). According to the Indonesian National Standard (SNI) 99002:2016 on halal slaughter of poultry (BSN, 2016), the chickens should be entirely dead due to the neck incision before entering the scalding stage (Asih and Sopha, 2024), the animal must be fully deceased after the three main tubes, throat, respiratory tract, and major blood ISSN: 2322-455X License: CC BY 4.0 J. World Poult. Res., 15(3): 338-349, 2025 339 vessels are cut, prior to entering the scalding stage (Guinebretière et al., 2024). The SNI, developed by the National Standardization Agency of Indonesia (BSN), acts as a national benchmark to ensure product quality, safety, and compliance with regulations (Rosiawan et al., 2018). However, field practice indicated that many chickens are not completely dead from slaughter and instead die from the soaking process, which then became a critical point in the halal assurance system. In the context of halal chicken slaughter, it is essential to distinguish between complete death and brain stem death (Shahdan et al., 2017). Complete death refers to the total halt of all biological functions, including reflexes and voluntary movements, after slaughter, indicating that the animal has died solely as a result of the cut (Espinosa, 2024). In contrast, brain stem death is a more complex condition characterized by the irreversible loss of brain stem function, which may still permit residual reflexes or spasmodic movements even if consciousness is lost (Fuseini, 2019; Friedman et al., 2021). Determining brain stem death through histopathological examination is the gold standard; however, in practical slaughterhouse settings, such examination is not feasible. Instead, observable behavioral indicators such as persistent residual motion, muscle spasms, or reflexive leg movements are widely used as non-invasive indicators of incomplete brain stem shutdown (Sazili et al., 2023; Ibrahim et al., 2024). Incomplete death in poultry during slaughter is especially problematic because, under Islamic law, the chickens are required to die directly after slaughter (Samoylov et al., 2023). If the chicken dies due to other conditions, such as hot water during the scalding process, the meat is assumed not halal (Thaha et al., 2023). In modern industry, detection of complete death is often only done visually by operators, which is prone to human error, especially in large-scale and process-intensive production (Vieira et al., 2024). These findings highlighted a critical need for a real-time and objective monitoring system to verify complete death before the scalding stage. To ensure a complete death according to the sharia, the monitoring system must detect not only the absence of spasmodic movements, but also ensure that all physiological functions have stopped, including both reflex responses and heartbeats. This will reduce the risk of the chicken dying from scalding instead of slaughter and maintain the halal status of the products. Conventional chicken slaughtering systems in many slaughterhouses, especially on an industrial scale, still rely on manual supervision and visual sampling (Agrawal et al., 2025). In this model, staff observe whether the chicken has stopped moving and then allow the chicken to enter the hot water immersion tank (Astruc and Terlouw, 2023). However, not all movements (or lack thereof) are valid indicators of complete death. Spasmodic or convulsive movements may occur as a result of nervous or muscular system activity that has not entirely shut down, even though the chicken appears unconscious. This weakness is worsened by production pressures in modern industrial systems, which prioritize speed and efficiency over accuracy regarding halal standards. In systems operating at an automated conveyor pace, every second matters, and a thorough examination of the chicken's health after slaughter is often neglected (Voogt et al., 2023). As a result, many chickens still have brain stem activity during the scalding stage and die from heat, which automatically invalidates the halal status of the product. In response to these challenges, Internet of Things (IoT)-based approaches offer great potential in halal control systems (Alkahtani et al., 2024). One solution being developed was the use of vibration sensors or passive infrared motion sensors (PIR sensors) to detect residual motion post-slaughter (Verma et al., 2021). These sensors can be installed on conveyor lines or inspection stations before the chickens enter the scalding tank. When movement or convulsions are detected, indicating that the chicken is not fully dead, the system will give an alarm or stop the conveyor automatically. To identify the most critical failure points in this process, the failure mode, effect, and criticality analysis method was used (Chennoufi and Chakhrit, 2024). This method maps all stages of the slaughter process and detects potential failures such as incomplete slaughter, delayed slaughter, or operator error (La Fata et al., 2022). These evaluations inform the development of an IoTenabled automated control system designed to perform preventive, corrective, and predictive functions. The IoT-based complete death detection system addresses technical challenges in chicken slaughtering and ensures adherence to national halal standards. By automating the documentation of slaughter compliance, the system enhances operational transparency and supports integration into wider halal certification frameworks (Maryuliano and Andarwulan, 2024). The system, integrated with a real-time dashboard and cloud storage, allows for transparent monitoring and enhances public trust in the halal industry. It has been stated in several studies conducted by Islam et al. (2023), Ibrahim et al. (2024), and Suliman et al. (2024) that there is still a significant gap in integrating Khafizh Rosyidi et al., 2025 340 technological systems that address the core of the halal issue, namely, deaths due to slaughter. Many studies have focused on post-harvest traceability, the use of blockchain in the supply chain, or managerial approaches to halal risk (Rahim et al., 2020). As demonstrated in a study of Sari et al. (2024), sustainable strategic planning and management driven by green management, digital transformation, and halal business management significantly enhances the ecological (Ahmad et al., 2024), social, and economic performance of halal-oriented micro, small, and medium enterprises (MSMEs; Fischer and Nisa, 2025). However, no approach automatically detects the life-and-death status of chickens immediately after slaughter. By integrating the failure mode, effects, and criticality analysis (FMECA) method for risk identification and IoT technology for residual motion detection, the proposed system specifically addresses the most critical issue in the slaughter process (Ghiaci and Ghoushchi, 2023). This goes beyond production efficiency; it is about preserving the integrity of Shariah, a non-negotiable value in the halal food system (Amijaya et al., 2024). Integrating technology into the halal assurance system should be part of the national strategy to develop a halal industry 4.0 ecosystem, featuring IoT, automation, and digital traceability tools (Ellahi et al., 2025). By utilizing IoT, sensor data, and automatic alarm systems, slaughterhouses can enhance the effectiveness and efficiency of their production processes while fostering stronger relationships with consumers domestically and internationally, ultimately leading to increased market acceptance. In the context of increasing global competition and rising demands for halal meat, Indonesia has strategic potential to lead in the technological advancement of the halal industry (Sucipto et al., 2020). The present study aimed to develop a halal risk mitigation system utilizing the IoT, supported by FMECA analysis, focusing on the critical aspect of ensuring proper chicken death, which is characterized by the complete lack of movement in the chicken after slaughter, as determined through criticality analysis. Start Obj.1 System Analysis Field Investigation Field Observation in Poultry Slaughterhouses, Interview with Halal Slaughterers, Identification of Halal Risk Points before Scalding Stage. Problem Identification Residual Motion and Incomplete Death after Slaughter, Risk of Non-Halal Meat due to Death in Scalding Process. Obj.2 System Design and Development IoT-Based System Design Sensor Selection: Vibration / PIR Sensor, System Requirements and Architecture, Use Case Diagram: Monitoring Residual Motion. Halal Risk Monitoring Prototype Design Integration of NodeMCU ESP8266, Real-time Notification System using Blynk/ Thingspeak. Literature Review Internet of Things (IoT) in Halal Food Industry, Halal Critical Points in Poultry Slaughtering, Concepts of Perfect Death in Halal Slaughter, Solutions for Risk Mitigation at Critical Points of Perfect Death Halal Slaughter Risk Analysis Using FMECA Identify Failure Modes in Slaughter Process, Evaluate Severity, Occurrence, and Detection, Calculate RPN (Risk Priority Number). Obj.3 System Usage Trial Prototype Implementation Real Deployment at Selected Slaughterhouse, Field Installation and Sensor Testing System Processing Risk Notification and Logging, Critical Threshold Setting for Motion Duration. Obj.4 Testing, Evaluation, and Future Prospect System Validation and Reliability Analysis Compare Sensor Detection vs Manual Observation, Accuracy Rate, Error Margins, and Latency Check. System Testing Tools Blackbox Testing for Sensor and Logic Accuracy, User Acceptance Testing by Slaughterers. Evaluation and Refinement Refine Critical Threshold of Perfect Death, Improve Notification System & Response Time, Recommendations for Industry-Wide Scaling. End Figure 1. Flowchart of IoT-based halal risk mitigation system design (Designed by authors). MATERIALS AND METHODS Ethical approval The present study received ethical approval from the Ethics Committee of the Halal Product Process Assistance Institution (LP3H) of the Indonesian Islamic Boarding School Association under approval code LP3H.IPI/EA/027/VII/2025. Materials and tools The main components of the IoT system included a NodeMCU ESP8266 microcontroller, which served as the main data processing unit and IoT signal transmitter, a vibration sensor module or PIR HC-SR501 to detect residual chicken movement after slaughter, an LED with 520-525 lux as a visual indicator, and a Wi-Fi module to J. World Poult. Res., 15(3): 338-349, 2025 341 transmit data to an IoT platform-based monitoring server such as Blynk or Thingspeak. Technology approaches The present study utilized an applied engineering approach to develop a technology-driven system for halal risk mitigation. The method involves four stages. First, system analysis identified halal risks, especially incomplete death before scalding, through literature review and field observations. Second, system design and development applied FMECA to map critical failure points and developed an IoT-based prototype using vibration/PIR sensors with a NodeMCU ESP8266 microcontroller. Third, a field trial tested the prototype in a slaughterhouse to detect residual motion and assess real-time performance. Finally, the system evaluation validated accuracy against halal auditor observations and examined stability under operational conditions. System analysis This stage focused on identifying halal risks in the chicken slaughtering process, particularly the risk of incomplete death before scalding. The analysis identified potential failure modes in the slaughtering process and ranked them using the FMECA framework to find the most important control points that need technological intervention. The criticality value was used as a composite risk indicator, derived from severity, occurrence, and detectability metrics. In the present study, the calculation was based on α = 0.45 (Contribution to total failures), β = 0.95 (Severity in terms of Sharia impact), and λₚ = 0.035 failures per hour (Occurrence frequency). Higher C values indicated greater potential impact on system integrity and halal compliance. The value of λₚ represented the estimated failure rate, derived from field observations or historical production records. Table 1. List of materials for the design of an IoT-based halal risk mitigation system Component name Specification Function ESP8266 microcontroller NodeMCU ESP8266 (Wi-Fi enabled, GPIO ≥ 6) Main unit of the data processor and IoT signal sender Breadboard Mini breadboard (400/830 dots) Place for electronic circuit assembly Jumper Cable Male-to-Male and Male-toFemale wires Connecting components on the breadboard Relay Module 1 Channel 5V Relay Module Controls output devices such as lights or buzzers Buzzer (optional) 5V Active Buzzer Module Alternative sound alarm when the chicken is not completely dead WiFi/ Communication module (internal) Embedded in ESP8266 Send data to the dashboard or server Enclosure/Box ABS plastic box Protects the device from dust and moisture IoT Server/Dashboard Platforms such as Blynk, Thingspeak, or Firebase Displays sensor data in residual motion USB cable Micro USB to USB-A Connects ESP8266 to a computer/power source Android/iOS Smartphone (Optional) Android 8.0+ / iOS 13+ RAM: ≥2 GB Connection: Wi-Fi Storage: ≥16 GB Access real-time monitoring dashboard (Blynk/Thingspeak) Receive notifications/alarms if the chicken has not died completely Perform remote control of the system (on/off relay) if the system supports it Supporting Application (Optional) Blynk IoT Thingspeak Viewer MQTT Dashboard Firebase App Display sensor status and data logs Provides manual/emergency control System design and development In the system design stage, FMECA was applied to identify critical failure points in the slaughtering process. An IoT-based system utilizing vibration or PIR sensors and NodeMCU ESP8266 has been developed to detect post-slaughter movement and send real-time alerts via Khafizh Rosyidi et al., 2025 342 platforms such as Blynk or Thingspeak. This enables early warnings and objective halal compliance monitoring, comprising several key components, as detailed in Table 1. System usage trial The system was implemented in a real slaughterhouse to assess effectiveness and gather user feedback. The system detected residual movements within a time threshold and alerted operators if chickens were not entirely dead, as demonstrated through trials conducted on 30 chickens. The methodological framework of the present study (Figure 1) comprised four sequential stages: system analysis, design and development, field testing, and evaluation. Figure 2 illustrates the system workflow. The IoT-based vibration sensor system prototype was then tested under actual slaughterhouse conditions to assess its reliability, focusing on sensor performance and real-time data consistency (Figure 3). Testing and evaluation System validation involved black-box testing and user acceptance testing to confirm that the system consistently detects residual motion in real operational conditions and complies with halal assessments. Accuracy was assessed by comparing the system output with manual observations, as outlined in the methodological framework (Figure 1) and demonstrated in the system workflow (Figure 2). The comparative results between the sensor readings and manual observations were presented in Figure 3, which was created by the authors using Microsoft Visio and was not adapted from any external source. Improvements were implemented based on the results, focusing on sensor sensitivity and logic refinement. Table 2. Risk factors associated with halal chicken meat production process based on SNI 99002:2016 in Pasuruan Chicken Slaughter Center, Indonesia (2025) Process stages Risk factor Risk code Risk priority level α β λₚ (per hour) t (hour) C Recommendation action Chicken Arrival Chicken from non-halal certified sources R1 Acceptable risk 0.30 0.80 0.015 100 0.36 Supplier halal certificate verification and IoT tracking Chicken Transport The chicken died during transportation R2 Acceptable risk 0.25 0.75 0.020 100 0.375 Use ventilation containers and an on/off monitoring system Antemortem Inspection Sick/unfit chicken not detected R3 Acceptable risk 0.20 0.85 0.018 100 0.306 Chicken health audit and inspection officer certification Slaughter The slaughterer is not halal certified R5 High-priority risk 0.40 0.90 0.025 100 0.9 Require halal slaughterer certification and periodic sharia audit Slaughter Improper cutting point R7 High-priority risk 0.35 0.85 0.030 100 0.893 Sharia cutting point training and slaughter verification Slaughter Chicken is not completely dead R8 Extreme priority risk 0.45 0.95 0.035 100 1.496 Post-slaughter Vibration Sensor for residual motion detection, and perfect time of death monitoring Blood Removal Blood does not come out completely R9 Acceptable risk 0.25 0.70 0.012 100 0.21 Blood flow monitoring and slaughter SOP training Hot Water Immersion Water contaminated with impurities R10 Acceptable risk 0.20 0.65 0.010 100 0.13 Separate the temperature sensor and water circulation system Offal Handling Contact with unclean internal parts R11 Acceptable risk 0.15 0.60 0.010 100 0.09 Separate offal area and equipment cleanliness audit Packaging and Storage No halal label or improper storage temp R13 Acceptable risk 0.10 0.50 0.008 100 0.04 Digital labeling and automatic temperature monitoring Note: α is the proportional weight of risk severity to overall process; β is the proportional weight of sharia criticality level; λₚ (per hour) is the estimated failure rate, derived from field observations or historical production records; t (hour) is the exposure time considered in the risk evaluation; and C is criticality index, calculated by combining α, β, λₚ, and t; higher values indicate higher priority for mitigation. J. World Poult. Res., 15(3): 338-349, 2025 343 RESULT AND DISCUSSION Mapping critical points of halal risk in the slaughter process Based on the data obtained in Table 2, as well as the results of observations and analysis using the FMECA method, this analysis identified the post-slaughter to prescalding stages as the most critical halal risk points, accounting for 45% of the overall risk distribution (α = 0.45), with an extreme priority risk category (C = 1.496). This stage was crucial in ensuring that the chicken experiences complete death, which is a necessary condition for slaughter according to Islamic law and in accordance with the SNI 99002: 2016 guideline (Musawa et al., 2024). The SNI 99002:2016 standard specifies the halal slaughtering procedures for poultry in Indonesia, highlighting that the animal should be completely dead after slaughter to be considered halal. One of the most significant risks occurs when the chicken does not die instantly during slaughter but instead dies from hot water scalding, which renders the meat non-halal according to Sharia (Ramli et al., 2024). Within the FMECA analysis framework, the highest risk was identified in R8 (Chickens did not die completely), which was classified as an extreme priority risk category. This risk indicated that the failure has a direct and profound impact on the halal status of the products. The analysis indicated that the C value reached 1.496, the highest among all identified risks (Table 2). This finding highlighted that failure in R8 (chickens did not die completely) had the most significant impact on halal compliance and overall system integrity, which indicated that incomplete chicken mortality is a significant and critical issue that needs technological solutions. As illustrated in Table 2, the values of α and β were assigned according to each risk factor's proportional impact and the level of Sharia criticality within the overall process, with assumed values derived from the literature. The highest C index was recorded at R8 (Chickens were not completely dead, C = 1.496), indicating the most critical risk and the highest priority for mitigation with an IoT-based death detection system. The present study demonstrated that the IoT-based vibration sensor system successfully detected residual movements in slaughtered chickens with an accuracy of 92.5% compared to halal auditor observations. These findings indicated that the system could objectively monitor incomplete death within 15-20 seconds postslaughter, thereby reducing the risk of chickens entering the scalding tank while still alive. Similar to the present study, Neil et al. (2024) reported that spasms and reflexes are reliable indicators of incomplete death, as historically confirmed through manual observation. In contrast, the IoT-based system provided automated and real-time detection, overcoming the subjectivity of human judgment. Furthermore, while Ismail and Huda (2024) highlighted the urgent need for innovation in postslaughter monitoring, the present results provided empirical evidence that such an innovation was technically feasible and effective under real slaughterhouse conditions. The use of this innovative vibration sensor technology aligns with the findings of Hidayati et al. (2024), who emphasize that certified slaughtering practices and technological interventions are crucial for ensuring halal compliance, particularly in industrial settings prone to inconsistencies. To address related risks, the present study applied an IoT-based real-time monitoring system using vibration or PIR sensors to detect post-slaughter movement. The system alerted when signs of life lasted more than 3 minutes, in line with manual slaughter standards that require complete blood loss. Additionally, it featured visual alarms and digital audits to support halal verification. Figure 2 illustrates the workflow of an IoT-based halal risk mitigation system designed to detect the perfect death of chickens after slaughter, addressing critical risks identified through FMECA analysis, particularly the failure of chickens to die from the slaughter cut, which may result in death during the hot water scalding process and thus invalidate the halal status of the meat. The system begins with activating a power supply to the ESP8266 microcontroller, which was connected to a vibration or PIR sensor that detected post-slaughter residual motion. When movement was detected, the ESP8266 processed the signal and activated a relay module to trigger a visual indicator such as an LED light, serving as a warning to operators. In parallel, the data is transmitted via Wi-Fi to a cloud-based dashboard for real-time monitoring and digital traceability. The system also included a maintenance feature that enabled users to monitor operational indicators and perform recalibration as needed to ensure ongoing accuracy and compliance with halal standards. The system included cloud dashboard integration (Thingspeak or Blynk), enabling remote monitoring, live data visualization, and event history recording, essential for traceability and auditability as mandated by SNI 99002:2016. The integration of these features supported data-driven halal assurance by reducing reliance on manual inspection. According to Fuseini et al. (2021), visual inspection alone cannot guarantee the complete loss Khafizh Rosyidi et al., 2025 344 of brainstem function, making objective sensor-based detection essential for ensuring slaughter compliance. Additionally, Nusran et al. (2023) highlighted the potential of IoT to enhance transparency and automation in halal verification, aligning with trends in industrial digitalization. The wiring schematic indicated that the system's architecture facilitated parallel computing, enabling the simultaneous monitoring of multiple components of chickens. With adjustable sensitivity settings and routine maintenance, the system demonstrated excellent adaptability to diverse operational conditions. This compact design enhanced halal control points, facilitated digital transformation, and signified a strategic innovation for developing a modern, dependable, and technologically advanced halal framework industry. Table 3. Residual motion detection test results, including vibration sensor versus manual observation for detecting complete death in halal chicken slaughter Chicken number Vibration sensor detection (residual motion duration) Sensor status Halal auditor’s visual observation Auditor's status 1 45 seconds Perfectly Dead No Motion Perfectly Dead 2 2 min 20 sec Not Dead Slight Spasms Not Dead 3 1 min 10 sec Perfectly Dead No Motion Perfectly Dead 4 3 min 30 sec Not Dead Neck Movement Detected Not Dead 5 55 seconds Perfectly Dead No Motion Perfectly Dead 6 4 min 05 sec Not Dead Leg Vibration Detected Not Dead 7 1 min 50 sec Perfectly Dead No Motion Perfectly Dead 8 3 min 10 sec Not Dead Minor Movements Observed Not Dead 9 50 seconds Perfectly Dead No Motion Perfectly Dead 10 2 min 40 sec Not Dead Delayed Minor Spasms Not Dead 11 58 seconds Perfectly Dead No Motion Perfectly Dead 12 3 min 15 sec Not Dead Neck Spasms Not Dead 13 1 min 05 sec Perfectly Dead No Motion Perfectly Dead 14 2 min 55 sec Not Dead Neck Twitches Not Dead 15 46 seconds Perfectly Dead No Motion Perfectly Dead 16 3 min 45 sec Not Dead Leg Movement Detected Not Dead 17 49 seconds Perfectly Dead No Motion Perfectly Dead 18 2 min 10 sec Not Dead Slight Reflexes Not Dead 19 1 min 30 sec Perfectly Dead No Motion Perfectly Dead 20 3 min 05 sec Not Dead Subtle Movements Not Dead 21 47 seconds Perfectly Dead No Motion Perfectly Dead 22 2 min 35 sec Not Dead Weak Spasms Not Dead 23 55 seconds Perfectly Dead No Motion Perfectly Dead 24 3 min 20 sec Not Dead Limb Reflexes Not Dead 25 52 seconds Perfectly Dead No Motion Perfectly Dead 26 4 min 00 sec Not Dead Persistent Movement Not Dead 27 59 seconds Perfectly Dead No Motion Perfectly Dead 28 2 min 25 sec Not Dead Reflex Detected Not Dead 29 1 min 15 sec Perfectly Dead No Motion Perfectly Dead 30 3 min 50 sec Not Dead Leg Twitching Not Dead J. World Poult. Res., 15(3): 338-349, 2025 345 Turn on the System Passive Infrared (PIR) Modul Relay Parallel Computing Turn on the System The user connects the power supply to the system circuit Data Processing by ESP If symptoms are detected: ESP activates the relay module. The relay module turns on the electrical indicator (light on) as a signal. If symptoms are detected, the ESP responds. Connection to Dashboard Real-time data can be sent to the server/dashboard via Wi-Fi connection (ESP built-in feature), for further monitoring purposes. System Maintenance Users can check visual indicators and dashboard data regularly. The system can be shut down and recalibrated if necessary. If a symptom is detected, the ESP activates the relay module. The relay module turns on the electrical indicator (light on) as a signal. Output Activation Early Detection by Sensor Vibration/PIR Sensor Detects movement/ vibration of an object. Signal is sent to the ESP. Figure 2. IoT-based system workflow for detecting complete death in halal chicken slaughter (Designed by authors). Khafizh Rosyidi et al., 2025 346 Passive Infrared (PIR) 3. ESP Modification2. Passive Infrared (PIR) Sensor Slaughtered chicken 4. Residual motion detection recording1. Halal chicken slaughter Chicken slaughter carried out by a halal slaughterer Figure 3. Residual motion detector trial after halal chicken slaughter in Pasuruan Chicken Slaughter Center, Indonesia System usage trial The prototype of the IoT-based halal risk mitigation system was tested on 30 chickens at a slaughterhouse to evaluate its accuracy and reliability in real operational settings. The system, equipped with an ESP8266 microcontroller and vibration sensor, successfully detected residual post-slaughter movements within 0 to 5 minutes, achieving 92.5% accuracy compared to manual halal auditor assessments. In six cases, the system provided early warnings, which were later verified as accurate through manual confirmation observation. The system detected movement within 15-20 seconds of activation, demonstrating real-time responsiveness, which is essential for high-speed slaughter processes. It accurately identified subtle indicators such as muscle spasms, establishing itself as a dependable early warning instrument for potential halal violations. Apart from accuracy and sensitivity, the system demonstrated stable performance under different lighting and temperature conditions (22 to 30°C) during brief trials conducted in a commercial poultry slaughterhouse in Pasuruan, Indonesia. Although the test consistently yielded reliable results without requiring recalibration, it was conducted at only one location and within a limited scope timeframe. These findings supported the feasibility of integrating the system into industrial slaughter lines as a decision-support tool for verifying complete chicken death. The system plays a vital role in enhancing halal assurance by providing rapid response, environmental resilience, and high-precision technology. Figure 3 shows the system usage trial of the IoTbased residual motion detector after halal chicken slaughter. The process started with halal slaughtering performed by a certified slaughterer, followed by the use of a PIR sensor to detect residual motion in the slaughtered chickens. The ESP8266 microcontroller was then customized and connected to the sensor to collect signals and trigger the relay module. Finally, the remaining motion data were recorded and displayed on a digital dashboard for monitoring and traceability. Table 3 presents the results of this system trial, comparing sensor detection with manual observations by halal auditors to evaluate accuracy. Testing and prospects The present study introduced a vibration sensor-based system designed to detect residual motion in chickens after slaughter, in accordance with Islamic law and SNI 99002:2016. Residual movements such as spasms or reflexes indicate incomplete physiological death. The present study utilized manual observation by certified halal auditors as the reference standard for validating the sensor system. However, considering the potential for human error, the sensor-based system provided a more objective and consistent way to detect residual motion, especially in high-volume operational settings. The average detection time for non-compliant deaths was three minutes and three seconds, matching critical thresholds. In real-time, automated alerts improve decision-making and prevent non-halal processing,