JES

Agriculture sector has been greatly inﬂuenced by the recent advances in electrical engineering. Nitrogen (N), from fertilizer, remains one of the largest input to surface and groundwater contamination, resulting in environmental and human health degradation. This paper explores the use of wireless potentiometry in ﬁeld settings for in situ N monitoring. We report a disposable IoT gardening soil sheet, capable of analyzing real–time soil nitrate concentration during leaching and irrigation events. The nitrate doped polypyrrole ion selective electrode (N-doped PPy ISE) sensor array sheet features a fault tolerant circuit design multiplexed to an oxidation and reduction potentiometer that can rapidly detect nitrate levels in soil leachates. Measurement data are transmitted via Waspmote ZB Pro SMA 5dBi radio, 6600mAh rechargeable battery, 7.4-volt solar panel

Majority of nitrogen (N) found in soils is contributed by animal waste and fertilizers. The most common form of nitrogen that is plant-available in soils is nitrate (NO 3 − ). Element nitrogen can also be present in soils as ammonium (NH 4 + ), nitrite (NO 2 − ), and or organic matter. As nitrate is a major limiting macronutrient for plant growth, it is often highly explored in detailed by agriculturalist. The high mobilizing property of the nitrate ions allows it to easily maneuver through soils, therefore leaching and running off into waterways. N in excess is subject to runoff and leaching into surface and groundwater during rainfall and irrigation. High nitrogen concentration in drinking water sources imposes a threat to humans when nitrates runoff into surface water; the buildup can lead to a polluted state toxic to marine life known as eutrophication. In 1 and, 2 researchers in China addresses special issues of eutrophication such as the increased activity of algal blooms and fish kills as well as investigate nitrate leaching under intensive vegetable garden production patterns. The conclusions indicate the need for innovative technology that can better monitor soil quality for the protection of the environment.
The standard laboratory techniques for determining total N, ammonium, nitrate, and nitrite are still the most commonly used. In, 3 these techniques are listed along with recommended test procedures for soil chemical analysis. These include potentiometric methods -explored in, 4-7 cadmium reduction, 8-10 ion chromatography, 11-13 steam distillation 14,15 and the hot KCL removal of N. [16][17][18] Techniques for in situ N determination using Time Resolved Raman Spectroscopy (TRRS) has been explored in, 19 however this technique is not the most popular among farmers. Although these techniques are highly accurate, they consists of expensive and time consuming lab procedures that can in some instances take days to obtain results. Nevertheless, commercially available technology for determining soil nutrients are increasingly becoming popular for its ability to allow quick and easy measurement of soil constituents that aid plant growth and those that cause aquatic pollution. However, these sensors are point of use only, meaning they can only account for concentration present in the area of the sample. Also, the technology is expensive for even most commercial farmers, therefore farmers can only afford one sensor unit per acre. One sensor per acre can prove inefficient because farmland can contain various terrain which can cause nutrient concentration to also vary among different areas. For these reasons, farmers are seeking alternative and more convenient methods to monitor the environment.
Specifically, an affordable sensing platform is needed that will allow accurate real-time quantification of spatially varied soil nutrient concentration for precision agriculture.
As defined by the United States Department of Agriculture (USDA), precision agriculture is an information based management system that is site specific and uses one or more of the following sources of data: soils, crops, nutrients, pests, moisture, or yield, for optimum profitability, sustainability, and protection of the environment. 20 The position and data dependent systems divide farmland into zones and gathers farm data inside the zones such as soil moisture, pH, and soil temperature. The data is sent to cloud via secure algorithm that monitors 60ft × 60ft zones to suggest best farming practices based on past and future predictions of soil quality and crop production. Unfortunately for large scale farms, high density subsurface sensing of soil chemistry has not been fully employed.
Recent advances in IoT have opened up the possibilities for networking arrays of sensors in order to obtain stochastic data on various soil components. The internet of things (IoT) is a global network of interrelated devices and objects which uses unique identifiers, such as an IP address, and the ability to transmit data over a network. Total number of IoT connections is expected to grow from 5 billion to 27 billion by year 2024. IoT has been deployed in agricultural settings for precision agriculture. [21][22][23][24][25][26][27][28][29][30][31] These IoT systems offer a range of services to farmers such as soil water management, environmental weather parameters, and tree and crop monitoring. IoT has given the farmer the ability to monitor and manage agricultural production via cellular device. To date, wireless sensor networks (WSN's) have been deployed in environmental and agricultural fields for numerous applications such as to manage water resources, 32 manage product storage facilities, determine optimal harvest time, characterize crop growth, and predict fertilizer requirements. Wireless sensor network has been deployed in 32 to monitor water content, temperature, and salinity of soil at a cabbage farm located in a semi-arid region of Spain. Temperatures at various positions in a feed warehouse were monitored using a wireless sensor network. 33 WSN using Zigbee has been used to monitor a greenhouse environment. [35][36][37][38] The energy limitations of wireless sensor networks also have been a focus. 34

Materials and Methods
Sensor sheets, prepared in-house, were printed onto a photopaper substrate with aqueous ink, which was formed using a combination of solvents. 41 The ink is composed of well-dispersed silver All solutions were prepared immediately prior to polymerization. Pyrrole is sensitive to ambient light and atmospheric oxygen. 40 Therefore PPy solution was refrigerated and not exposed to light.
Three soil samples (L1, L2, and L3) were collected from three 12m 2 garden beds at Florida International University's Modesto-Maidique Campus in Miami, Florida. Soils were identified via the USDA -NRCS's Web Soil Survey as limestone-derived udorthents. They have a gravelly-loam texture, shallow to bedrock and poorly drained. Experimental plants were grown from seeds, twelve inches apart directly into garden bed soil, while controlled group were grown in 10 L pots of bare loamy soil with no added fertilizers or microbes. All groups were grown under 100% sun with irrigation, weed and pest control done as needed. The Shurflow water pump transferred fluids from the storage tank to the sprayer with an inlet pressure of 2.06 bar (30 psi) and an output flow rate of 4 gallons per minute, providing test beds with water through DIG drip irrigation.
Potentiostat circuit.-The input range for the potentiostat circuit (Fig. 2) depend on the values of R1, C1, R2, R3 and the source of input (BATT or USB), there by having a direct control over the input voltage of the potentiostat. For instance, a 5 volt input will yield a linear input range in the −1 to + 1 V range. The circuit supports a power supply range of 3V to 32V. Range of output current sensing is depended on the negative voltage to resistor R5. An applied voltage of −3.7 V yields a range of −150 to 120 μA (at −5 V range is −210 to 65 μA). Alternatively, current sensing range can also be tailored by introducing variable resistors at positions R5 and R6. Power dissipation of the circuit was calculated as the products of voltage and current of all the power sources. Total power dissipation at ideal state is 50 mW. The current drawn internally by op amp (X3) is −18.9 nA and the current drawn internally by op amp (X5) were found to be −23.34 nA).

Results and Discussion
Electrodes were inkjet printed on a paper substrate. Working electrodes were modified for nitrate sensitivity by electrodeposition of pyrrole. As a result a thin film polymer membrane of N-doped pyrrole was formed capable of soil nitrate measurements. A prototype sheet that comprises of 8 electrodes in a 5 × 3 inch area was developed (Figs. 1a, 1b). Working electrodes of the individual sensors are coupled to a custom potentiostat (Fig. 2) via a TCA9548A 1-to-8 I2C multiplexer module using a flex connector. Electronic sensing is enabled via a microcontroller and an IoT network. Individual electrodes are engaged by the potentiostat for a certain duration by varying the control signals and time delay appropriately.
Nitrate sensitivity, detection range and the stability of the electrodes were found to have an influence on the properties of electrodeposited sensors. A constant current applied for a duration of 5-20 minutes yielded nitrate sensitive working electrodes. Pre-treatment of electrodes in 10 mM KOH solution improved the hydrophilicity of substrates, which also helped in forming a uniform electrodeposited layer. Electrodeposited electrode sheets were incubated at 70 • C for 15 min for enhanced stability.
Figs. 3a, 3b shows circular grains around 50-200 nm in diameter for 5 and 10 minute (E 5 and E 10 ) long electrodeposition. At longer electrodeposition times, larger clusters were observed (Figs. 3c-3d). The non-uniformity and nonconductive nature of the larger clusters were found to hinder the ionic exchange during electrochemical measurements. Linearity and sensing range was found to be affected by the duration of electrodeposition. Electrodes deposited for 15 min (E 15 ) were found to have a linear response in the 5 ppm to 90 ppm nitrate levels. Fig. 4a shows the differential pulse voltammetry (DPV) current response of sensors to varying nitrate levels. Nitrate sensitivity of sensors that were electrodeposited at varying times is depicted in Fig. 4b. As the films grew thicker, the slope of the nitrate response curve was found to be higher nearing a Nernstian response. Apparent from the sensor response, the electrodes that were electrodeposited for a duration of 15 minutes was found to have the best linear sensitivity as compared to the other electrodes. Apparently from the sensor response slopes, electrode E 15 was found to be more than 110% sensitive to nitrate levels as compared to E 5 and E 10 . However, electrode E 20 was found to be the least sensitive among all the electrodes, despite having a larger area. We assume that the non-uniformity and nonconductive nature of the larger clusters are hindering the ionic exchange during electrochemical measurements. Fig. 5 depicts the amount of leached nitrate as detected by the sensor. Three different soil types of limestone-derived udorthents with known carbon and nitrogen contents (Table I) were used for this  study. Sensors were installed one inch beneath the top of the soil beds. Readings were taken 600 seconds after irrigation allowing time for leachate to come in contact with the sensor. Soil samples, spiked with 100 mM nitrate solution, were used for leaching studies. Irrigation was applied at a fixed daily rate and the leachate samples from the bottom drain were analyzed for six consecutive irrigation cycles. The response of the sensor to varying irrigation cycles reflected the leaching rates. Leaching trends were found to be very similar for all three soil samples. Leaching was found to be highest for the first 2 irrigation cycles. This can be due to loosely bound nitrate. Depending on the nitrate leach rate, the sensor response has been categorized into three; LOW: 5-40 ppm, MED: 40-100 ppm, HIGH: 100-300 ppm (Table I). When the response of the sensor is HIGH for two consecutive times, an alert signal is sent out by an external micro-controller to the IoT network. However, stability of the sensor was found to be degrade after 3 consecutive tests. This can be due to the deterioration of the pyrrole surface from the mud particulates in the leachate.
Waspmote Agriculture Sensor Board Pro serves as the microcontroller and the IoT network. Data packets are transmitted via a Waspmote ZB Pro SMA 5dBi radio, 6600mAh rechargeable battery, 7.4-volt solar panel, and a Meshlium ZigBee PRO access point. Data obtained from individual sensors are directed to Meshlium access point and stored directly to the hard drive or sent to a cloud service. Meshlium is a Linux router which works as the gateway to the waspmote sensor network. Inserting a sim card onto the waspmote sim slot allows for data and commands to be transmitted to cellular devices. A ZigBee radio transmit data frames to the meshlium, which operates at 2.54 Ghz, using a transmission power of 50 mW and a line of sight 5dBi dipole antenna to cover a range of 7000 meters. Out of three soil samples tested, all of them showed HIGH leachate levels consecutively for two irrigation cycles. A leaching rate > 100 ppm of leaching for two consecutive cycles (Cycle 1 and 2). After Cycle 3, the leachate level was found to drop consistently. Similar trend was observed with samples 2 and 3. Hence, re-fertilization of the soil will be based on the crucial information from our soil sheet sensor.

Conclusions
We developed a IoT enabled soil sensor sheet sensor capable of electrochemically detecting nitrate leachates. The sensor sheet was inkjet printed on a paper substrate and modified via electrodeposition. Initial studies indicate that the analytical current response is linearly proportional to soil leachate nitrate content, however, the stability of the sensor was found to be degrade after 3 consecutive tests. This can be due to the deterioration of the pyrrole surface from the mud particulates in the leachate. Sensor deterioration can be due to various reasons, such as concentration of soil nutrients, pH, ionic composition, non-specific adsorption on the surface of the electrode, weather conditions, and soil microbial interaction. Currently, we are addressing the sensor abnormalities as observed from our experiments. The potential of our wireless sensing platform was demonstrated by detecting the soil leachate levels in three samples of limestone-derived udorthents with respect to irrigation cycles. Measurement data are transmitted via Waspmote ZB Pro SMA 5dBi radio and a Meshlium ZigBee PRO access point to cloud server and mobile device.