In our day today life, we see that most of the people fall down when the situations are not normal. The abnormal situations can be either due to sickness or due to sudden injury. Sickness can be a chest pain, faint, vomiting, headache, etc., and sudden injury can be due to sudden fall on the ground due to slippage, fire accident, etc., Analysis shows that most of the abnormal situations of the humans are accompanied by a fall from their original or normal position. The fall of elderly people has become more common and the injuries caused by fall may be so severe such that the person may not be in a position to ask for help, which may be life threatening too. Hence the detection of a fall which is an abnormal activity from the normal human activity is more important for automated geriatric care and health care systems. The algorithm used to detect the abnormal human activity should be accurate because the normal activities should not be detected as an abnormal activity. In this paper, a review is made on the automated fall detection systems used for smart home systems and for automated health care systems.