Technology has been developing every day in human life. The need for the advancement of technology is to lead human life comfortably. The use of the Internet of Things is changing the face of development in all sectors of human life and it can be used for the successful implementation of energy-efficient buildings and hence lead to a total reduction of electrical energy consumption in different aspects of human life. Due to the presence and increase in smart home technology, have led to an increase in the need for intelligent learning of the inhabitants and detecting their activities such as security, energy-efficient automation, and resource management.

Until now, many African developing nations where energy is improperly used for home and other reasons have not made good use of IoT. Due to inefficient appliance use and imprecise occupancy monitoring, power consumption has grown to be a significant issue. Hence, in order to give the required answer, various smart sensors are installed in a home to automate the home and to detect motion and occupant activity to ensure energy efficiency. In order to forecast future energy demand, the support vector machine (SVM) technique is employed to record the energy usage.

The evaluation results of the system show that the proposed systems provide a smart home with energy efficiency compared to the non-smart house energy system and thus the recommendations for smart houses for households in developing countries in Africa. Keywords: IoT, Smart Home, Energy Efficient, Energy Consumption Prediction.