The rapid developments of the electronics sector across the world have resulted in a drastic increase in electronic waste (e-waste). Electronic products are discarded as trash after the end of the life period. The volume of e-waste is significantly increasing in Oman and its management is a serious concern. The main challenges associated with e-waste management include excessive generation and overfilling, a lack of streamlined process for e-waste collection and classification, and finally a lack of e-waste data that is required for tracking the progress of their collection and recycling. Hence, Oman needs a smart system for automatic collection and processing, which would improve the transparency and planning of the volume of waste, by enabling estimate and prediction techniques. This paper presents a research agenda for developing a smart system to handle e-waste and the preliminary insights. The study findings include the results of the literature review, the business opportunities, and the proposed deep learning model for e-waste classification. The paper concludes with the future work which includes the smart bin development for e-waste collection, its technical components, and the implementation methods.