## 3 Communication in IoT
### Commonly Used Sensors for Smart Farming and Heavy Metal Identification
As an alternative method for rapid heavy metal detection, Portable X-ray Fluorescence (PXRF) was used to assess cumulative concentrations of soil heavy metals based on linear regression models between fluorescence intensity and specific heavy metal concentration. Due to its ease of use and rapid testing ability using non-destructive quantification, PXRF has been widely used by researchers in numerous domains [110; 111; 112; 113]. For the heavy metal assessment in agricultural soil conducted by [PERSON] et al. [109], VNIR sensor was used to anticipate soil properties comprising pH, soil nitrogen, and carbon [114; 115]. In addition to PXRF, NixPRO color sensor can also be used to identify hotspots and total spatial area in excess of environmental thresholds in landfill soils [116]. Lately [PERSON] and [PERSON] [117] have developed a Portable Electrochemical System (PES) for on-site heavy metal detection on farmland. Their system was composed of a three-electrode configuration which comprised a signal acquisition system integrated with a microcontroller-based potentiostat to perform square-wave anodic stripping voltammetry. Their system was assessed by testing the detection of pd(II) and cd(II) in acetic acid soil extracts and acetate buffer solution [117]. However, their system did not include any wireless sensor module to transmit heavy metal composition data. Other than the aforementioned sensors, there are several other wireless sensors dedicated to: photosynthesis, i.e., Beta Therm temperature sensor; leaf wetness sensor, i.e., SLWA-M003; precision sensor for leaf temperature, i.e., \(\Delta\)LA-C; light intensity sensor, i.e., BH1750 FUI sensor [118; 119; 120; 121; 122]. With the advent of these sensors, CO\({}_{2}\) sensors also play an essential role, especially in greenhouse systems [123]. CO\({}_{2}\) sensors have also been widely used to measure the subsequent level in peat soil, landfill, and forest control site [124; 125]. In the smart farming ecosystem, the growth and quality of the fruit bunch cannot be neglected. In this regard, there are dedicated fruit growth monitoring sensors which researchers have used in their domain of plantation. [PERSON] [126] designed an optoelectronics sensor for monitoring fruit and stem radial growth. Their developed sensor was lightweight and easy to install with low maintenance. Nonetheless, the sensor was well tested in open field conditions. In addition to this, the effect of gas concentration during the fruit growth was studied by [PERSON] et al. [127], for which a smart ethylene electrochemical sensor was established to investigate ethylene emission from fruits. Lately, [PERSON] et al. [128] came up with a heat field deformation sensor to measure sap flow dynamics through the tomato peduncle. Heat griddling of the peduncle was performed to differentiate flow of xylem and phloem with respect to developing fruits. Capacitive sensors calculate SM on the basis of changes in soil capacitance due to differences in water content [129]. Commercial UTs use capacitive sensors, which are usually more accurate than resistive sensors but cost more [130]. Ground Penetrating Radars (GPR) [131] are based upon electromagnetic wave absorption and reflection. SM sensing uses impulses, frequency sweeping, and frequency-modulated technologies. This method is used for measuring soil moisture near the surface (up to 10 cm). The most reliable soil humidity samples used in fields are neutron scattering samples [132] and scattering samples use radiation methods for calculating SM by estimating changes to the neutron flux density due to water content of the soil [133; 134]. However, in such cases, specific licenses are required to carry out its implementation. Numerous research studies have been performed to develop electrochemical devices for various applications, which are known as potentiostat [135; 136; 137; 138; 139; 140; 141].