# Isotropic IoT-Based Magnetic Flux Density Meter Implementation for ELF Field Measurements +
## 1 Introduction
In [26], a free-standing inductive harvester for use in locations with ambient magnetic fields caused by far-off and/or difficult-to-reach conductors is presented. Researchers introduced a self-powered wireless sensor by utilizing ambient 50 Hz magnetic fields in High Voltage (HV) substations. The laboratory experimental results have shown that the proposed magnetic field harvester of the sensor can deliver a useful average power of 300 \(\upmu\)W when placed in a magnetic flux density of 18 \(\upmu\)T (RMS). Based on numerous experiments using different inductors and combinations of current-carrying conductors, the authors in [27] offer a feasibility analysis of energy harvested from stray electromagnetic energy of household AC power lines. The results are encouraging since it is possible to harvest up to 2 mW of power using simple components for the harvester implementation. The study in [28] presents two distinct configurations evaluated in situ along a Norwegian railway and in a controlled laboratory setting to support the viability of magnetic field energy harvesting (MF-EH) in electrical railways. The power output of the proposed system can reach up to 40.5 mW at 50 Hz when positioned near an emulated section of a railway carrying 200 A, based on the experimental measurements carried out at the laboratory. In a region with moderate traffic, the prototype system harvests 109 mJ from a single electric train, yielding an estimated daily energy output of 1.14 J. Another magnetic field energy harvester (MF-EH) application for railways is presented in [29] to power wireless sensors for condition monitoring. In that study, an MFEH system was designed, enhanced, and tested for energy harvesting from the rail tracks' traction return currents. The magnetic core was created using two flux collectors to partially enclose the rail track based on the dispersion of the magnetic field around the rail track. Measurements show that the MFEH's power output was decreased by reducing eddy current loss by positioning it farther from the rail track. The experiment's power output decreased from 5.05 to 1.6 W when the MFEH was relocated from a distance of 48 mm to 190 mm, where the eddy current loss was insignificant. In this work, the implementation of an isotropic Extremely Low Frequency (ELF) IoT-based meter is presented. The proposed low-cost meter can measure the magnetic flux density from 100 nT with three identical sensor probes for isotropic field measurements in the X, Y, and Z planes, enhancing the work in [30]. The proposed device has an almost flat response across the frequency range from 40 to 10 kHz, detecting and measuring several magnetic field sources, including the public power supply network and its harmonic frequencies. In our approach, an Arduino UNO Wi-Fi Rev.2 board is used for data transferring from the sensor to the cloud as a complete IoT solution, supported by the Blynk application via Android and iOS operating systems or web interface. Furthermore, an ELF energy harvesting (EH) circuit was also proposed in our study for the utilization of the alternating magnetic fields (50 Hz) derived from the operation of several consumer devices such as transformers, power supplies, hair dryers, etc. using low-consumption applications. The rest of this article is organized as follows: the proposed magnetic flux density meter operating principles are presented and analyzed in Section 2. Section 3 gives the full description of the electronic circuit (analogue section) of the proposed EMF meter. Section 4 is devoted to the description of the isotropic ELF sensor implementation. A demonstration of real-time ELF field monitoring as a proposed IoT solution via the Blynk application is presented in Section 5. Section 6 is devoted to the description of the magnetic field utilization derived from the operation of common-use electrical devices, such as a hair dryer at the laboratory using a proposed MFEH harvester, and finally, Section 7 includes the conclusions and a discussion on future work.