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Ubiquitous street lighting is essential for urban areas. While nowadays, LED-based “smart lamps” are commercially available, municipalities can only switch to them in the long run due to financial constraints. Especially, older types of lamps require frequent bulb replacements to maintain the lighting infrastructure’s function. To speed up the detection of defects and enable better planning, a non-invasively retrofittable IoT sensor solution is proposed that monitors lamps for defects via visible light sensors, communicates measurement data wirelessly to a central location via LoRaWAN, and processes and visualizes the resulting information centrally. The sensor nodes are capable of automatically adjusting to shifting day- and nighttimes thanks to a second sensor monitoring ambient light. The work specifically addresses aspects of energy efficiency essential to the battery-powered operation of the sensor nodes. Besides design considerations and implementation details, the paper also summarizes the experimental validation of the system by way of an extensive field trial and expounds upon further experiences from it.

The Internet of Things (IoT) enables various applications by providing means to capture environmental effects and possibly control some part of the environment. This is also true for different Smart Farming applications and as a result various systems are available. However, when designing a measurement campaign for a certain task, it becomes obvious that the current products lack flexibility to build the best solution using a single system. This concerns available communication options but also the option to add further sensors for specific tasks. In this paper, we present a modular platform for IoT nodes that can be configured as needed for different applications. We first present our concept and then highlight the ability to use different communication options, power options and the ability to integrate further sensors via adaptation modules. In addition, we show two example use cases that, based on the state of the art, would require multiple parallel systems.