Introduction: The aging of the world population is accompanied by a substantial increase in neurodegenerative disorders such as dementia. Early detection of dementia, i.e. at the mild cognitive impairment (MCI) stage, could be an essential condition for slowing down the loss of autonomy and quality of life caused by the disease, as it would provide a critical window for the implementation of early pharmacological and non-pharmacological interventions. However, the current assessments for MCI have several limitations. In this context, approaches involving smart home technologies offer many attractive advantages, including the continuous measurement of functional abilities in ecological environments. Objective: This systematic review aims to investigate the current state of knowledge on the effectiveness of smart home technologies for the early detection of MCI through the monitoring of everyday life activities. Methods: A systematic search of publications in Medline, EMBASE, CINAHL was conducted. Results: Sixteen studies were included in this review. Twelve studies were based on real-life monitoring, with several sensors installed in participants' actual homes, and four studies included scenario-based evaluations in which the participants had to complete various tasks in a research lab apartment. In real-life monitoring, the most used indicators of MCI were walking speed and activity/motion in the house. In scenario-based evaluation, time of completion, quality of activity completion, number of errors, amount of assistance needed, and task-irrelevant behaviors during the performance of everyday activities predicted MCI in participants. Discussion: Despite technological limitations and the novelty of the field, smart home technologies represent a promising potential for the early screening of MCI and could support clinicians in geriatric care.