Dr. Steve Liang (梁鴻翎) is a researcher, teacher and entrepreneur. Dr. Liang is currently a professor at the University of Calgary and director of the GeoSensorWeb Laboratory. Steve’s goal is to build a world-wide sensor web, make its information accessible and useful and to empower anyone to build connected applications by using the information generated from the world around them for positive impact at a global scale. For example, Steve is the editor of the Open Geospatial Consortium SensorThings API and the result of the standard work is to provide a uniform way to expose the full potential of the Internet of Things.

Steve has been an invited speaker at universities and industries around the world. In 2013, Steve was chosen one of Calgary’s Top 40 Under 40 by the Avenue Magazine. Steve held the AITF-Microsoft Industry Research Chair on the Open Sensor Web from 2011 to 2014.

I have been a Postdoctoral fellow in the GeoSensorWeb Lab at the University of Calgary since 2015. I have been a Member of the OGC (Open Geospatial Consortium) Architecture Board since 2020. I received my Ph.D. in 2013, from the Multi Mobile Sensor System Research Team, University of Calgary, in positioning, navigation and wireless location on smartphones. I have my B.Sc. and M.Sc. in Geomatics and Civil Engineering from the University of Tehran, Iran. My interests are primarily in the field of 'sensor fusion' and 'intelligent geospatial computation' in context-aware location-based services. Sensor technologies are used almost everywhere. Connecting multi-sensor over a network increases the quality, coverage, confidence and usability of their data in real-time applications. Multi-sensor data, along with the IoT’s access to cloud-based processing resources, will lead to a tremendous expansion in the online accessibility of geospatial services anytime and everywhere.

New technologies have allowed us to conduct research at larger and larger scales, but our ability to manage such scales becomes more complex and difficult. By re-using some of the lessons learned by major technology companies like Facebook, Yahoo!, Etsy, and Bloomberg, we can take configuration management from cloud tech and apply it to sensor device tech. By managing our devices with a centralized tool, we can set up devices with less work.

Other web tech can be used to simulate and test geo-sensor networks, allowing us to design and build more robust networks that can respond to changing network and environmental conditions.

Recent innovations in an internet of things(IoT) technology have allowed researchers to collect large and highly accurate datasets on the environment while vastly decreasing the time and cost of gathering such data. However, researchers need more stable, scalable, lower cost sensor monitoring network and more powerful monitor data processing and analysis system. By nature IoT applications are dynamic and, thus, complex and being difficult to build. Devices can be lost at any time. So does the network connection. Therefore, a new IoT architecture should be intended to meet these requirements. Based on existed technology, is possible to design an IoT architecture, which suits the environmental monitoring, using open source hardware and software. The IoT architecture contains several components. 1) Devices: It records the ecological parameters with different kinds of field sensors and actuators; 2) Gateway: It connects sensors to the world and manage the hardware and software running at the edge.3) Cloud: It is a place where process and analyze the field data; 4) User-front-end: Researchers can see the general monitoring information and data analysis result. This information will appear in a variety of charts and integrates with map.

I am a Geomatics Ph.D. student at the University of Calgary with a background in Electrical Engineering and Bio-Electric Engineering. I am experienced in embedded systems programming, implementation and testing (IoT application), digital signal/image processing; machine learning algorithms; and familiar with iOS application development. My interest in getting benefit of Internet of Things (IoT) in improving and easing system management has motivated me toward expanding my knowledge in software development, and system architect design.

I am a GIScientist with an engineering background and experience in GIS development. I am experienced in Geospatial software development to facilitate mobile mapping, 2D/3D data visualization, network analysis, and spatial data management. To keep the connection with industry, I have led the software development team of the Geomatics Department of K.N.Toosi in several industrial MobileGIS projects. My research in Master was focused on how to improve the quality of Location Aware Recommender Systems using high quality Volunteered Geographic Information (VGI) as well as automation of VGI quality assessment. My background in VGI and the Internet of Things(IoT) led me to study on Location-Based Social Network (LBSN) and IoT integration network models. Having added to GSWL, I broadened my technical knowledge to employ IoT and Artificial Intelligence (AI) to develop real-time GIServices.

I am always passionate to develop IoT/GIServices and leverage cutting edge technologies such as AI to solve real-world spatial problems.

I am a Ph.D. student who has started my Ph.D. in the GeoSensor Web lab, at the University of Calgary, since January 2020. My background is in Geomatics Engineering. I have experience in Geodesy, navigation, positioning, signal, and image processing. Broadly, my research interests include the Internet of Things (IoT) and Artificial Intelligent (AI). We live in an era where AI is becoming a global platform for the computation and interaction between smart objects in real-time applications and many critical aspects in our daily life. With the application areas such as smart health, smart cities, and smart homes in IoT, AI can be considered as a complementary package of smart networked objects. AI brings a promise of genuine interaction.

Software developer, architect, and integrator with project management, consulting, and technical management experience. Manages software development at the GeoSensorWeb Lab. Specializing in web applications, APIs, sensor data processing and geomatics visualization tools in the cloud (SensorUp Explorer on AWS). Handles DevOps to AWS using Terraform and utilities in Node and Bash.