Collecting, storing, and providing access to Internet of Things (IoT) data are fundamental tasks to many smart city projects. However, developing and integrating IoT systems is still a significant barrier to entry. In this work, we share insights on the development of cloud data storage and visualization tools for IoT smart city applications using flood warning as an example application. The developed system incorporates scalable, autonomous, and inexpensive features that allow users to monitor real-time environmental conditions, and to create threshold-based alert notifications. Built in Amazon Web Services (AWS), the system leverages serverless technology for sensor data backup, a relational database for data management, and a graphical user interface (GUI) for data visualizations and alerts. A RESTful API allows for easy integration with web-based development environments, such as Jupyter notebooks, for advanced data analysis. The system can ingest data from LoRaWAN sensors deployed using The Things Network (TTN). A cost analysis can support users’ planning and decision-making when deploying the system for different use cases. A proof-of-concept demonstration of the system was built with river and weather sensors deployed in a flood prone suburban watershed in the city of Charlottesville, Virginia.
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iMOST: An IoT Framework for Energy Efficient Street Lights
The amount of greenhouse gas emissions from streetlights is equivalent to 2.6 million cars with as many as 26 million streetlights in the United States. The proposed IoT controller integrates sensors to make these streetlights as hubs for smart environment monitoring with effective energy usage. Conservation of energy is one of the main concerns in the modern era, and energy coming from the sun can be utilized efficiently alongside a smart streetlight management system instead of conventional streetlight management techniques. Additionally, with streetlights being present throughout a city, the opportunity to collect city-wide weather data is proposed. To this end, a solar-powered IoT-based smart street lighting and environmental monitoring system is proposed. The proposed energy-efficient IoT-based system uses a microcontroller to control light-emitting diode (LED) streetlights depending on lighting conditions and vehicle detection, ensuring that the streetlights can be turned on when needed.
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- Award ID(s):
- 1924117
- PAR ID:
- 10451152
- Date Published:
- Journal Name:
- 2022 IEEE 8th World Forum on Internet of Things (WF-IoT)
- Page Range / eLocation ID:
- 1 to 2
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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