Faculty of Computing

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Author: search.filters.author.Liyanage, SHas files: Yes

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    PublicationOpen Access
    Gesture driven smart home solution for bedridden people
    (Association for Computing Machinery, 2020-09-21) Jayaweera, N; Gamage, B; Samaraweera, M; Liyanage, S; Lokuliyana, S; Kuruppu, T
    Conversion of ordinary houses into smart homes has been a rising trend for past years. Smart house development is based on the enhancement of the quality of the daily activities of normal people. But many smart homes have not been designed in a way that is user friendly for differently-abled people such as immobile, bedridden (disabled people with at least one hand movable). Due to negligence and forgetfulness, there are cases where the electrical devices are left switched on, regardless of any necessity. It is one of the most occurred examples of domestic energy wastage. To overcome those challenges, this research represents the improved smart home design: MobiGO that uses cameras to capture gestures, smart sockets to deliver gesture-driven outputs to home appliances, etc. The camera captures the gestures done by the user and the system processes those images through advanced gesture recognition and image processing technologies. The commands relevant to the gesture are sent to the specific appliance through a specific IoT device attached to them. The basic literature survey content, which contains technical words, is analyzed using Deep Learning, Convolutional Neural Network (CNN), Image Processing, Gesture recognition, smart homes, IoT. Finally, the authors conclude that the MobiGO solution proposes a smart home system that is safer and easier for people with disabilities
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    PublicationEmbargo
    Smart wheelchair to facilitate disabled individuals
    (IEEE, 2019-12-05) Jayakody, A; Nawarathna, A; Wijesinghe, I; Liyanage, S; Dissanayake, J
    This paper describes the design and implementation of a voice controlled smart wheelchair for disabled whom the manual operation is difficult due to lack of physical strength. The main objective of this research is to develop a smart wheelchair to facilitate disabled individuals which can be operated with lesser effort while operating the wheelchair. The proposed wheelchair can be controlled through voice commands which enables the user to control the wheelchair with less effort. This aids the disabled in carrying out daily activities independently within indoor environments. The proposed solution has five modules namely, speech recognition module, obstacle avoidance module, autonomous navigation module, health monitoring module, and central system controller. The wheelchair operates in two modes called manual mode and the autonomous mode. This paper presents a smart wheelchair that makes the disabled individuals' life easier with technology. Further this paper elaborates testing and evaluations carried out to prove the proposed title.