*1.3.2 Factors responsible for low productivity*

Existence of Big Farmers: Even though India's Zamindari system has been abolished, rural large farmers continue to play a shadow role. These large landowners control rent, tenure, tenancy rights, and other aspects of renters' lives. As a result, the situation of tenants is deteriorating day by day. It is quite difficult to increase productivity using solely modern technologies in this type of tenure structure.

High Land-Man Ratio: Huge demographic pressures characterize Indian agriculture. According to the 2001 Census, over 72.2 percent of the entire population lived in rural areas, with agriculture employing nearly three-quarters of the total rural working population, or nearly 228 million employees (out of 310.7 million workers).


Surface 30–40%

Sprinkler 60–70%


**Table 2.**

*Water losses in percentage in India.*

*An IoT-based Immersive Approach to Sustainable Farming DOI: http://dx.doi.org/10.5772/intechopen.105449*

**Figure 2.** *Frequency of occurrence of drought in various parts of country.*

Uneconomic land subdivisions occur as a result of population growth. All of these factors contribute to low production.

Rural Environment: In India, the rural social milieu is a major contributor to low productivity. Farmers in India are lethargic, illiterate, superstitious, have a primitive outlook, are conservative, unfit, and resistive to modern farming methods. Farmers' marginal productivity in agriculture is zero, due to the family-based farming method. Credit and marketing facilities that are irregular and insufficient: According to Raj Krishna's research, poor farmers are unable to effectively spend money in the land during the peak season of agriculture due to a lack of and insufficient availability of agricultural loans at a low rate of interest. Furthermore, crop marketing is regulated by intermediaries or touts. As a result of all of this, agricultural productivity was low. Modern technologies are lacking: In India, over 60% of cultivable land lacks irrigation facilities. In 2000–2001, only 75.14 million hectares (out of 87.94 million hectares) were irrigated. As a result, the green revolution's 'Package Program' is ineffectual across the vast majority of India's gross cultivated areas. Degradation of the Ecosystem: According to the Indian government, 329 million hectares (almost half of the country's land) have already been degraded. This leads to a yield loss of 33 to 67%. Furthermore, 5% of the land has been ruined to the point where it can no longer be utilized.

**Figure 3** shows that interest in this issue has grown over time as measured by the number of papers published every year. The smaller number of papers for 2019 is

**Figure 3.** *Annual number of articles presenting IoT irrigation systems that have been published [2].*

owing to the fact that the year was not quite through when the paper selection procedure was concluded. As a result, not all of the papers written in 2019 have been published.

#### *1.3.3 Water management*

There are various ways to distribute water irrigated agriculture is a type of agriculture that uses water as a source of input. The effectiveness of the various possibilities varies, in some circumstances, a specific technique for a given crop should be adopted. Irrigation can be done in a variety of ways, but they can all be categorized into the following groups: When it comes to how water is spread, we can examine the flood irrigation, (ii) spray irrigation, (iii) drip irrigation, and (iv) nebulizer irrigation. On the subject of sensing systems, we can discuss I unplanned irrigation, in which the amount of water is not calculated or estimated; (ii) planned irrigation, in which the water is supplied according to estimated demands over a year; and (iii) adhoc irrigation, in which the amount of water is estimated based on sensor readings. The great majority of the papers in this section propose to distribute water using pumps and valves in conjunction with sensors that assess ambient conditions in order to determine water needs. In this part, 83 of the 89 reviewed articles include detailed information about the planned irrigation system, while the remaining six just state that irrigation actuators are present (see **Figure 4**). There are 49 articles that just indicate that their system has motors/pumps (40 papers) or valves (nine papers) without providing any additional information. 19 of the studies that provide additional information use sprinklers (the most common irrigation technique) [3–21], eight utilize drip irrigation [22–30], two propose sprayers [22, 31], and the rest use highly specialized irrigation systems or it can be used on multiple systems [32]. Three papers [16, 18, 27] suggest using a fogging system in conjunction with the main irrigation system, whereas two papers [17, 28] suggest using fertigation in their systems.

#### *1.3.4 Major applications*

Every aspect of traditional agricultural methods can be significantly transformed by incorporating cutting-edge sensor and Internet-of-Things (IoT) technologies into farming practises. Smart agriculture has the potential to reach previously unimagined heights thanks to the current seamless integration of wireless sensors and the Internet *An IoT-based Immersive Approach to Sustainable Farming DOI: http://dx.doi.org/10.5772/intechopen.105449*

**Figure 4.** *Number of papers that propose different irrigation systems [2].*

of Things. By utilizing smart agriculture approaches, IoT can help improve answers to many traditional farming difficulties, such as drought response, yield optimization, land suitability, irrigation, and insect management. **Figure 5** depicts a hierarchy of critical applications, services, and wireless sensors in smart agriculture applications. While key examples of how modern technology might aid in improving overall efficiency at various levels have previously been covered.

The Internet of Things (IoT) is beginning to affect a wide range of sectors and companies, spanning from manufacturing to health, communications, energy, and agriculture, in order to reduce inefficiencies and improve performance across all markets. When you think of the word, two words come to mind: [34, 35]. Current applications appear to be simply scraping the surface of IoT's potential, with the full extent of its influence and applications still to be seen. Given the recent increase, we may expect IoT technology to play a vital role in a number of agricultural applications. This is due to the capabilities of the Internet of Things, which include basic communication infrastructure (used to connect smart objects to sensors, vehicles to user mobile devices via the Internet), as well as a variety of services such as local and remote data collection, cloud-based intelligent information analysis and decision making, user interfacing, and agriculture operation automation. Such people have the power to change agriculture, which is currently one of our economy's least efficient sectors. **Figure 6** displays the important technology drivers in smart agriculture, whereas **Figure 7** depicts the major technological implementation roadblocks.

#### *1.3.5 Demand for water*

The water demand of the irrigation system is determined by estimating the amount of water required for best crop output. The estimated crop evapotranspiration (ETc) is used to determine the water demand; however, estimating the ETc requires knowledge of the reference evapotranspiration (ET0). ET0 was defined by Dorenbos

**Figure 5.**

*A hierarchy of applications, services, and sensors exists for smart agriculture [33].*

**Figure 6.** *Major challenges in technology implementation for smart agriculture [33].*

*An IoT-based Immersive Approach to Sustainable Farming DOI: http://dx.doi.org/10.5772/intechopen.105449*

**Figure 7.** *The agricultural industry's key technological drivers [33].*

and Pruitt [36] as a result of the total amount of under ideal conditions, water evaporated from the soil and a large area of grass-covered ground transpired a large amount of water (vigorous development and unrestricted access to water). The Penman–Monteith equation is the most extensively utilized approach [37], was used to calculate ET0, as illustrated below [2].

$$ET0 = \frac{0.408\,\Delta\,(Rn - G)\frac{900\,\text{ y }u2\,\,(\sigma - \alpha)}{T}}{\Delta + \chi\,(1 + 0.34u2)}\tag{1}$$

The ET0 value is measured in millimeters per day, Rn is the net solar radiation incident on the crop surface, G is the soil heat rate (MJ/(m<sup>2</sup> day)), is the psychrometric constant (kPa/C), u2 is is the steam pressure slope, expressed in kPa/C. is the wind velocity recorded at a height of two metres, es is the saturated steam pressure, and ea. is the actual steam pressure, all in kPa. Agrometeorological stations measured all climate factors to determine ET0, which is dependent on wind speed, sun radiation, air temperature, and relative humidity.

ETc was calculated using ET0 and the crop coefficient as inputs (Kc). The type of crop, the climatic circumstances, the soil's distinctive features, and the vegetative phase are all taken into account by Kc. The CNR (Chilean Irrigation Commission) bulletins [38, 39], as well as the paper headed "Reference Evapotranspiration, for the Determination of Water Demands for Agriculture in Chile" [40], tabulate values for each species and growth phase. Eq. (2) was used to compute crop evapotranspiration, ETc, where ET0 was changed based on the crop coefficient:

$$ET\_c = K\_c ET\_0 \tag{2}$$

The crop coefficient is Kc, while ET0 is measured in millimeters per month (millimeters per month). The monthly net water demand was calculated using the Eq. (ND). ND is calculated using the difference between ETc and the crop's effective rainfall (Pe). ND refers to the water required by the crop's roots from the irrigation system.

$$\text{ND} = \text{ET}\_{\text{c}} \text{-P}\_{\text{c}} \tag{3}$$

The United States Department of Agriculture's Natural Resources Conservation Service (NRCS) developed a method for calculating Pe based on real rainfall [36]. It was estimated in this study using the monthly average of actual rainfall data from the national agroclimatic network (Agromet) [41]. Because any irrigation system water losses must be compensated, the irrigation system must provide more water than the net water demand (ND). Certain security elements were also implemented to ensure that the crop received at least the ND. The effects of deep percolation and surface runoff are factored into the drip irrigation system's application effectiveness (Ea), which was determined to be 90% efficient. Two further elements that influence water demand are the washing requirement (RL) and the coverage coefficient (Kr). The minimal amount of percolation water required to maintain a constant soil salinity and avoid an increase in salinity that could stymie crop development is known as RL. Water does not require to be applied to the entire anticipated surface of the crop when Kr is used. The value of Kr is determined to be less than or equal to unity. Equation shows the water requirement [2].

$$D = \frac{ND \ (1 + Rl) \ Kr}{Ea} \tag{4}$$

The irrigation schedule specifies how frequently and for how long water must be provided to the crops. The irrigation frequency interval and volume of water provided are determined by the amount of water kept in the root zone of the crops and how quickly it is consumed. The soil texture, soil structure (water percolation), effective root zone depth, crop type, and crop growth stage all influence irrigation frequency [3]. For high-frequency watering requirements, a short interval is defined (one, two, or more days). The goal is to maintain a consistent soil humidity [4]. The annual irrigation schedule, which detailed the frequency of irrigation for each month, was presented by an irrigation consultant. The daily irrigation demand (RID) in liters was calculated using Eq. (5) once the irrigation calendar was defined.

$$\text{RID} = \frac{\text{DAc}}{\text{Di}} \tag{5}$$

where Di is the number of irrigation days each month and Ac is the number of hectares of land covered by the crops. Ac was calculated using Eq. (6), which took into consideration the surface of each plant frame (PF) as well as the quantity of plants (Nplants)

$$A\_c = \text{PFN}\_{plants} \tag{6}$$

The length of time (ti) for which an irrigation system may run in order to provide enough water to meet the needs of the crops was determined using Eq. (7).

*An IoT-based Immersive Approach to Sustainable Farming DOI: http://dx.doi.org/10.5772/intechopen.105449*

$$ti = \frac{RID}{qeNe} \tag{7}$$

where *qe* is the volume flow rate supplied by the emitters in liters per hour, and *Ne* is the number of emitters [2].

#### *1.3.6 Irrigation System's electricity demand*

Drip irrigation, a water-saving irrigation technique that distributes water to crops through a pressurized network of valves, pipelines, and emitters, is one of the most widely used irrigation systems. The irrigation system pump is chosen based on the irrigation system head (necessary pumping pressure) and the amount of water that the crops demand. The irrigation system head takes into account the elevation head, the pressure drop due to friction in the pipes and singularities (i.e., valves), and the required working pressure by the emitters. The pump's electrical demand remains constant since the pumps in this study deliver a constant volume flow rate. Other research [5, 6, 42] suggested using a variable speed pump to modify water flow in response to changes in solar radiation, allowing for an enhanced irrigation regime. A control system that aligns water supply with solar radiation could aid energy optimization [7], particularly in offgrid environments; however, this option is not explored in this study. The optimal design achieves the lowest overall cost, which includes the operational cost (electricity cost) of pumping, which lowers as the pressure drop decreases, as well as the capital cost of the irrigation system. Pipe friction and singularity losses in valves and fittings are used to compute the pressure drop. The pressure reduces as the pipe diameter increases, cutting the operational cost; nevertheless, the capital cost climbs in lockstep. Reduced pressure loss can also be helped by selecting the right emitters and filters.

The pumping system was designed to manage the worst-case scenario, which occurred during the peak water demand month. The operational characteristics of the pump were determined using the pump characteristic curve, which was produced during an experimental standard test. The pump characteristic curve provided information on the system head (H), pump efficiency (), and electrical power required by the pump (Wp) as a function of the pumped volume flow rate of water (Q). Eq. (8) was used to calculate Wp:

$$\mathbf{W}p = \frac{\mathbf{Q}\rho\mathbf{g}H}{\eta p\eta m} \tag{8}$$

where ηp denotes the efficiency of a mechanical pump and m denotes the efficiency of an electric motor. In general, ηp was between 90 and 95 percent, and m was between 45 and 65 percent. Some high-efficiency pumps can attain up to 85 percent total pump efficiency (ηp ηm). Eq. (9) was used to compute the daily electricity requirement (Ed) once Wp was estimated (from Eq. (8):

$$E\_d = \mathcal{W}\_p t\_i. \tag{9}$$

#### *1.3.7 Solar PV system design*

Irrigation water demand is frequently seasonal, throughout the year, the PV system generates electricity. The solar PV system should be able to deliver the electricity required by the irrigation system in order to ensure a uniform distribution of the volume flow rate of water required by all crops. Reliable data on solar resources is required for proper PV system design. In this investigation, the Solar Explorer, an online tool developed by Chile's Ministry of Energy [10], was used. The Solar Explorer's solar PV model is used in this study. It's based on a Sandia National Laboratories model, which is outlined in the reference. Solar radiation data for each unique location was also collected using the Solar Explorer, which was then incorporated in the solar PV model. The reference goes into great detail on the radiation database and its accuracy. Internet of Things Research: Key Technology and Applications In this paper, the author discusses the importance of IoT and RFID. With proper administration and dependable transmission, IOT can connect all items anywhere, at any time. There are several strata to be found.

