Heterogeneous LoRa-Based Wireless Multimedia Sensor Network Multiprocessor Platform for Environmental Monitoring

Abstract

The acquisition of data in protected natural environments is subordinated to actions that do not stress the life-forms present in that environment. This is why researchers face two conflicting interests: autonomous and robust systems that minimize the physical interaction with sensors once installed, and complex enough ones to capture and process higher volumes of data. On the basis of this situation, this paper analyses the current state-of-the-art of wireless multimedia sensor networks, identifying the limitations and needs of these solutions. In this sense, in order to improve the trade-off between autonomous and computational capabilities, this paper proposes a heterogeneous multiprocessor sensor platform, consisting of an ultra-low power microcontroller and a high-performance processor, which transfers control between processors as needed. This architecture allows the shutdown of idle systems and fail-safe remote reprogramming. The sensor equipment can be adapted to the needs of the project. The deployed equipment incorporates, in addition to environmental meteorological variables, a microphone input and two cameras (visible and thermal) to capture multimedia data. In addition to the hardware description, the paper provides a brief description of how long-range (LoRa) can be used for sending large messages (such as an image or a new firmware), an economic analysis of the platform, and a study on energy consumption of the platform according to different use cases.

Wireless Sensor Networks for Water Quality Monitoring: A Comprehensive Review

“…Wireless network devices for WQM are often located in remote or hard-to-reach areas, without power sources available. Therefore, to address this difficulty, they are equipped with batteries that allow them to extend their lifetime to the maximum [68]. Applications such as those described in [62], [65], [66], [69], use this approach.…”

“…Applications such as those described in [62], [65], [66], [69], use this approach. To maximize the lifetime of each node, duty cycling techniques are used [70] so that they are active only for the time necessary for parameter acquisition, data processing, and transmission [71], the latter being the most energy-consuming process [68].…”

Heterogeneous LoRaWan deployment for application dependent IOT networks

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