Body posture is one of the most important parts when lifting an object as it can causes injury if the wrong technique and body posture were used. A worker will injure their low back if a bad posture is not in consideration. A good body posture is recommended among workers to reduce the chance of injury while lifting and improve their postural safety. The main objectives of this study are to observe the body posture of the worker during lifting and study the comparison of using lower back support when lifting. It also investigates the muscle activity of the worker during heavy lifting using EMG and simulates the worker's movement using CATIA Software for Rapid Upper Limb Assessment (RULA) results. The selected grocery was chosen in Kota Samarahan, Sarawak with 7 male respondents are identified to undergo this study. The results show that the worker with lower back support tends to show raw EMG signal with lower muscle activity compared to without using lower back support. Thus, using belt support can reduce muscle activity by up to 67.4% compare to not wearing back support. Raw EMG signals also show 3010 amplitude (mV) muscle activity if postural safety of the workers improved by following the NIOSH lifting Recommendations.
Environmental indoor air quality is one of the major concerns in occupational safety and health issues related to workers. Nowadays, the evolving of Internet of Things (IoT), the monitoring of the surrounding environmental desired parameters is more fascinating with the use of various sensors. Real time data now can be monitored with the Wi-Fi connection where the data being transfer across the network cloud with different platform service. This research focus is on the environmental monitoring for indoor air quality in terms of carbon monoxide (CO) in selected palm oil mill factory. This project aims to benefit the workers in a way where air quality is monitored. This low-cost device air quality monitoring (LCDAQM) used an ESPduino-32 to collect and process sensed data to the ThingSpeak platform service that can be monitored through web based or apps. The level of the carbon monoxide (CO) will light up the red LED when reach more than 50ppm which was set by OSHA. Result shows that level of CO in factory is unhealthy and need future engineering control action. The validation between LCDAQM and RS CO meter show the percentage error of 14.41%. Therefore, this study will help workers and factory to monitor and reduce the occupational safety and health (OSH) related problems to indoor air quality in factory.