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Human safety has become one of the most targeted field for the researchers, owning it to its grave importance and the increased competition in the market for human safety gadgets. Hundreds and thousands of human safety devices (HSD) are being developed because of the rapid advancement in the field of Internet of things (IoT) that involve sensing technologies, embedded systems, wireless communication technologies, variety of sensors etc. An essential function of these devices is human activity recognition (HAR). Present human safety devices continuously track human activities with the help of sensors and track down any unusual activity by performing sensor data analysis (SDA)using machine learning (ML) algorithms. This paper aims at reviewing the latest reported systems for human safety and listing down the various sensors that can be used in human safety devices to detect unusual activities along with the machine learning algorithms that are used for the sensor data analysis.