Deploying wireless sensor networks (WSN) in rural environments such as agricultural fields may present some challenges that affect the communication between the nodes due to the vegetation. These challenges must be addressed when implementing precision agriculture (PA) systems that monitor the fields and estimate irrigation requirements with the gathered data. In this paper, different WSN deployment configurations for a soil monitoring PA system are studied to identify the effects of the rural environment on the signal and to identify the key aspects to consider when designing a PA wireless network. The PA system is described, providing the architecture, the node design, and the algorithm that determines the irrigation requirements. The testbed includes different types of vegetation and on-ground, near-ground, and above-ground ESP32 Wi-Fi node placements. The results of the testbed show high variability in densely vegetated areas. These results are analyzed to determine the theoretical maximum coverage for acceptable signal quality for each of the studied configurations. The best coverage was obtained for the near-ground deployment. Lastly, the aspects of the rural environment and the deployment that affect the signal such as node height, crop type, foliage density, or the form of irrigation are discussed.

The presence of illicit discharges in sewerage systems generates an important impact in wastewater treatment plants and the ecosystem. In this paper, we present two prototypes for monitoring the presence of solids in wastewater and to study the effect of the water height. The prototypes are based on color and infrared LEDs and two photosensors located in the prototypes at 0° and 180° degrees. When the photosensor is located at 180°, all color LEDs present a good range of output voltage (approximately 5 V to 0 V) and good R2. However, for the typical concentration of solids in wastewater, the prototypes do not work correctly. When the photosensor is located in the prototypes the LEDs, yellow, red, and white have a good operation with voltage differences of 1.73 V, 1.76 V, and 1.13 V in P1 and 1.58 V, 1.84 V, and 1.35 V in P2, respectively. We calculate the mathematical model with the heights and solid concentration. The mathematical models which do not consider height present good R2. In conclusion, when the photosensor is located in the prototype, the height does not have an important effect and can detect the illicit discharge of solids. When the photosensor is located at 180°, it can be used for water with important changes in solid concentrations.

Soil moisture control is crucial to assess irrigation efficiency in green areas and agriculture. In this paper, we propose the design and calibration of a sensor based on inductive coils and electromagnetic fields. The proposed prototypes should meet a series of requirements such as low power consumption, low relative error, and a high voltage difference between the minimum and maximum moisture. We tested different prototypes based on two copper coils divided into two different sets (P1–P15 and NP1–NP4). The prototypes have different characteristics: variations in the number and distribution of spires, existence or absence of casing, and copper wires with a diameter of 0.4 or 0.6 mm. In the first set of experiments carried out in commercial soil, the results showed that the best prototypes were P5, P8, and P9. These prototypes were used in different types of soils, and P8 was selected for the subsequent tests. We carried the second set of experiments using soil from an agricultural field. Based on the data gathered, mathematical models for the calibration of prototypes were obtained and verified. In some cases, two equations were used for different moisture intervals in a single prototype. According to the verification results, NP2 is the best prototype for monitoring the moisture in agricultural lands. It presented a difference in induced voltage of 1.8 V, at 500 kHz, between wet and dry soil with a maximum voltage of 5.12 V. The verification of the calibration determined that the calibration using two mathematical models offers better results, with an average absolute error of 2.1% of moisture.

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Illegal dumpings in sewerage can cause problems in wastewater treatment plants, so it may become an environmental problem. In this paper, we propose a system for detecting these illegal dumpings. We use conductivity sensors for detecting a change in the conductivity of water because this change may appear due to a dump. The system is based on two coils. One of the coils is powered by a sinus-wave and the other coil is induced. To prevent damage from water in the copper we encapsulate the coils in a PVC tube. These coils are connected to a Flyport in order to send the values and generate alarms. We tested the prototype with different configurations of coils with encapsulation of 3 and 1 mm. When the encapsulation is of 3 mm, we do not observe differences in the induced voltage. The prototype selected has a difference of 4.10 Volts between the samples 0 and 40 g/l of the table salt. In the verification test this prototype has a relative error of 2.54%.