Citizen Science is research undertaken by professional scientists and members of the public collaboratively. Despite numerous benefits of citizen science for both the advancement of science and the community of the citizen scientists, there is still no comprehensive knowledge of patterns of contributions, and the demography of contributors to citizen science projects. In this paper we provide a first overview of spatiotemporal and gender distribution of citizen science workforce by analyzing 54 million classifications contributed by more than 340 thousand citizen science volunteers from 198 countries to one of the largest online citizen science platforms, Zooniverse. First we report on the uneven geographical distribution of the citizen scientist and model the variations among countries based on the socio-economic conditions as well as the level of research investment in each country. Analyzing the temporal features of contributions, we report on high “burstiness” of participation instances as well as the leisurely nature of participation suggested by the time of the day that the citizen scientists were the most active. Finally, we discuss the gender imbalance among online citizen scientists (about 30% female) and compare it with other collaborative projects as well as the gender distribution in more formal scientific activities. Online citizen science projects need further attention from outside of the academic community, and our findings can help attract the attention of public and private stakeholders, as well as to inform the design of the platforms and science policy making processes.

Recent developments in space-based surveying methods of the Earth's topography, including the differential interferometric synthetic aperture radar (DInSAR), have increased the availability of options for monitoring land subsidence. However, DInSAR methods require expert knowledge and specialized software, and they are time-consuming. Here, we demonstrate that a land subsidence signal can be identified in the differences in the freely available global digital elevation models (e.g., SRTM and TanDEM-X) using a simple statistical method. This finding opens up a venue to develop a computer application to identify land subsidence or uplift of a few decimeters per at least a decade order. Such an application enables monitoring the effects of underground mining, seismic/tectonic movements, landslides, volcanic activities, and similar effects on the Earth's topography. It can also provide a valuable and cost-effective tool for studying land deformation.

The Sustainable Development Goals of the United Nations strive to maximize development needs, while minimizing environmental deterioration, without jeopardizing the needs of future generations. Nevertheless, due to urbanization, the escalating trend in natural-resource use, particularly electricity and water, is currently a crucial challenge for sustainable development. One of the promising options is the smart home, which is an extension of building automation with smart characteristics in monitoring, analyzing, controlling, and cloud computing with networked smart devices. Due to the lack of appropriate infrastructure and conscious consumption, its global adoption in the construction industry remains low. We present a technical feasibility of a multi-functional experimental smart home to support the Sustainable Development Goals of the United Nations in terms of water and energy conservation. The layered architecture of the cloud platform with an application program interface enables seamless integration of heterogeneous smart-home technologies and data sources. Use cases demonstrated its capacity to conserve electrical energy and water resources in support of the United Nations’ Sustainable Development Goals. Aside from that, the smart home’s electricity self-consumption of at least three autonomy days was confirmed with zero emissions and electricity bills, and a reduced supply-water consumption.

This research project aimed to develop a software program or an interactive dance motion analysis application that utilizes modern technology to preserve and maintain the Sarawak traditional dance culture. The software program employs the Microsoft Kinect V2 to collect the digital dance data. The proposed method analyses the collected dance data for comparison purposes only. The comparison process was executed by displaying a traditional dance on the screen where the user who wants to learn the traditional dance can follow it and obtain results on how similar the dance is compared to the recorded dance data. The comparison of the performed and recorded dance data was visualized in graph form. The comparison graph showed that the Microsoft Kinect V2 sensors were capable of comparing the dance motion but with minor glitches in detecting the joint orientation. Using better depth sensors would make the comparison more accurate and less likely to have problems with figuring out how the joints move.