Abstract: This disclosure relates generally to root zone moisture estimation for vegetation cover using remote sensing. Conventionally, it is challenging to estimate root zone soil moisture using only satellite data. Moreover, estimation of soil moisture under vegetation cover based on bare surface soil moisture and vegetation parameters is not available. The disclosed method and system facilitate estimation of an ensemble of soil moisture under vegetation cover and root zone soil moisture using process based soil water balance for spatial estimation of root zone soil moisture. The system estimates bare surface soil moisture for different soil types/textures using the baseline bare surface model and soil properties derived from satellite data and in-situ sensors. The method further provides temporal spatially distributed soil moisture inputs to an intelligent irrigation management/information system which is very important to reduce and regulate water consumption.

Abstract: Stubble burning is a serious problem resulting in pollution attributable to smog, loss of nutrients in the top soil, and risk of fires spreading out of control. Existing methodologies have attempted to predict burning areas, but have failed to do so because of inefficient sensing mechanism. Present disclosure proposes a system and method to compute burning index score pertaining to crops by detecting harvest season and predicting probable areas of burning by combining current year's crop area map along with harvesting period and historical hot spot information. Computation of the burning index score is accomplished based on inputs received from at least one of satellite imaging, multi-spectral drone based sensing devices and crowdsourcing information. This will help to prioritize the area for taking corrective measures such as training of farmers, availability of resources, optimizing the resources schedule, etc.

Abstract: This disclosure relates to methods and systems for high resolution and scalable crop yield forecasting by first developing a first crop yield forecasting model to generate coarse resolution yield maps and further dynamically selecting a set of pixels from the coarse resolution yield maps. The coarse resolution yield maps, satellite, weather and soil related data are fed as input to a second crop yield forecasting to generate high resolution crop yield forecasting maps. Further, domain knowledge about crop growth stages, economically important crop growth stages and weather based triggers are identified to quantify extent of change in crop yield. This helps in crop yield forecasting during real time adverse weather conditions. Finally, an adjusted crop yield model is obtained after adjusting losses incurred due to the real time adverse weather conditions to obtain accurate high resolution crop yield forecasting maps. The method of present disclosure is inexpensive, light-weight, and scalable.

Abstract: Plant health estimation is required to be performed so as to detect any health issues in early stages, so as to take counter measures. Existing systems for the plant health estimation perform the health estimation by considering data obtained from satellite images of the plants being monitored. However this alone may not be much effective as the satellite images fail to provide information on many parameters which have direct or indirect impact on health of the plants. Disclosed herein are a method and a system for plant health estimation, wherein the system performs health estimation at a macro level and a micro level. The macro level health estimation is done using satellite images of the plants as inputs, whereas the micro level health estimation is done by collecting and processing sensor data with respect to various parameters that affect health of a plant.

Abstract: This disclosure relates generally to estimating age of a leaf using morphological features extracted from segmented leaves. Traditionally, leaf age estimation requires a single leaf to be plucked from the plant and its image to be captured in a controlled environment. The method and system of the present disclosure obviates these needs and enables obtaining one or more full leaves from images captured in an uncontrolled environment. The method comprises segmenting the image to identify veins of the leaves that further enable obtaining the full leaves. The obtained leaves further enable identifying an associated plant species. The method also discloses some morphological features which are fed to a pre-trained multivariable linear regression model to estimate age of every leaf. The estimated leaf age finds application in estimation of multiple plant characteristics like photosynthetic rate, transpiration, nitrogen content and health of the plants.

Abstract: A method and system for synthesizing smartphone cue-cards representing socio-technical system (STS) service design prototyping based on a plurality of constraints has been provided. The system creates just in time, a dynamic visual design for senior and junior designers for displaying of patterns as digital Cue Cards based on human configured time constraint and novelty constraints all the while avoiding repeatability for the designer. Smartphone is utilized as a mechanism to host multiple cue cards and an interaction model which allows multiple cue-card-connectedness to jump across constraints of local-maxima/minima towards a global-maxima/minima. The method allows young designers get access to better long term memory (LTM) and senior designer getting access to faster LTM. The present disclosure helps senior designer get faster access to new patterns to reduce time for novel new interventions.

Abstract: Socio-technical system (STS) service design is an approach to design that consider human, social and organizational factors, as well as technical factors. Due to the nature of STS, any human effort will have challenges in terms of time and resource constraints in such a scenario. A method and system for designing the STS service at scale has been provided. The present disclosure is configured to bring efficiency in terms of time taken and efficacy in terms of dimensions covered. The system uses machine learning methods and natural language processing to aid the rapid process transformation of design thinking for STS. The system is using machine intervention for dimensionality reduction, helps in giving a weighted approach towards goal achievement irrespective of human biases. The prototype is expressed in a commonly understandable human language helping in prototype evaluation—visualizing the prototype even before it is built.

Abstract: Coarse resolution satellite data has limited information content of land captured in the images and small area field boundary detection is technically challenging. Embodiments of the present disclosure provide a method and system for detection of field boundaries using coarse resolution satellite data and GIS. Multi-layer crop segmentation approach is used over RoI, wherein agricultural land related segments are derived from a soil layer, a temporal stack for a current season and a temporal change layer from the coarse resolution satellite data of the RoI. Segmentation based on different aspects captures various details at each segmentation layer. The segments are then combined, which aggregates all information related to the land to accurately detect the field boundaries in the RoI. The field boundaries are further refined using GIS topology operations. Baseline cadastral maps are updated using information from maps generated using refined field boundaries identified in real time for each season.

Abstract: State of the art authentication mechanisms have limitations when used by Basic Emergent User (BEU). Embodiments herein provide method and system for recognition based multi-skill-multi-sensory passwords with dynamic identification of sensor combination based on end user skill, specifically for the BEU. The method disclosed generates user profile using a task-based technique to determine skill and capability of the user associated with each of a plurality of sensory categories used for generating a multi-skill-multi-sensory password. Each of the plurality of sensory categories are graded is descending order based on user's skill and capability and user is offered to select each password entry from a particular sensor category in accordance with the identified grade in each iteration. Thus, the entropy of password generation in the context of user is split among the sensor categories.

Abstract: This disclosure relates generally to automated methods and systems for assessing moral hazard and adverse selection in agricultural insurance that assist an insurer, re-insurer by generating recommendations for adoption of crop protocols using the dynamic Crop Protocol (DFI) engine of insurance companies during the crop cycle (CP). A moral score is computed based on an adoption index, a crop health index and a weather index. The moral hazard score is further used to dynamically determine a moral hazard level that indicates a correlation between one or more parameters derived from the acquired data and classified as low, moderate, and high based on the correlation. The method of present disclosure aids to under-write the insurance and associated risk based policy effectively and efficiently for determining eligible claim payout to minimize manual error and mitigate faulty loss assessment.

Abstract: State-of-the-art techniques hardly attempt to address controlled resource access problem in context of Basic Emergent Users (BEUs). Embodiments of the present disclosure provide a method and system for Proof of Work (POW) based protection of resources. The method includes using the POW for work done by BEUs in physical world and mapping it to digital world to generate crypto currency in terms of credit score, wherein an end user is eligible or authorized to use a resource of an entity to get a desired service if accumulated credit score is above a credit threshold. Gaining points to improve the credit score is challenging as it is based on percentage of compliance achieved by the BEU through actual work in accordance with a compliance protocol. Further, the method includes authenticating the authorized user based on a set of questions with increasing difficulty, derived based on a culture graph.

Abstract: The present disclosure relates to methods and systems for generating optimal coverage plan to perform agricultural activities by farm workers. The present disclosure determines optimal deployment plan considering the constraints such as limited human farm workers, complete agricultural activities within given time frame, optimizing cost, and so on. The entire farm or the plot is divided to smaller units such as sub-plots and agricultural activities required for each sub-plot are identified. Then, the uniform clusters are formed from the sub-plots such that the given constraints are satisfied, using a uniform distribution algorithm. An optimal routing algorithm is employed to determine the optimal path for each uniform cluster. Lastly, the uniform clusters are assigned to the farm workers to perform the agricultural activities, and the deployment coverage daily plan is generated using the optimal path for each cluster, so that total traversing time to cover the sub-plots is minimized.

Abstract: Agriculture is impacted due to various parameters that results into heavy losses to the crops. Existing methods rely on manual inventories from fields and statistical results are prone to errors thus classification of crops may not be accurate. Present disclosure provides systems and methods for detection and prediction of disguised and potential non-performing assets (NPAs) in agriculture. Disguised NPAs detection involves, obtaining satellite data from sources and natural calamity, detecting of crop for past years, crop growth, estimating yields, market prices for individual years, AC zones, etc. wherein a generate performance score is generated for each field for classifying crop as disguised NPA.

Abstract: This disclosure relates generally to assessing soil carbon sequestration. One of the driving factors for climate change and global warming is emission of greenhouse gas emissions. Of the possible ways to reduce climate change and global warming adoption, sustainable agricultural practices will enable efficient soil carbon sequestration thereby reducing the greenhouse gases as well as increasing the crop yield. The disclosure is a method and a system for real time assessing soil carbon sequestration of farm based on remote sensing. The soil carbon sequestration of farm is assessed by continuously monitoring the farm at real time based on remote sensing using a plurality of satellite data and a plurality of farming data using several techniques. The several techniques utilized for assessing soil carbon sequestration includes machine learning, a carbon sequestration estimation technique, estimating a crop health index and an adoption index and computing a set of carbon sequestration parameters.

Abstract: State of art techniques mostly rely of computationally intensive, time consuming Neural Networks. Embodiments provide a method and system for identification and classification of different grain and adulterant types for grain grading analysis. The method analyzes input image of grain sample of elements to determine morphological features of elements, using dynamically determined calibration factor from reference object in the image. Variation in perimeter of elements is used to perform classification of elements into target grain size, low size adulterants and higher size adulterants. The aspect ratio of target grain determines grain variety and adulterants determine adulteration percentage. Elements are classified into grain colored and non-grain colored adulterants. Grain colored adulterants are further classified as Grain Like Impurities and non-GLI, using predefined ranges of standard deviation of perimeter metric.

Abstract: The agricultural lending decision making process is complex due to various issues. Most of the financial institutions relied on subjective analysis to assess the credit risk of borrowers. A method and system for assessing credit worthiness of a farmer and risks associated with a farm have been provided. The credit worthiness of the farmer and risk associated with farm is assessed by aggregating data which significantly influence the farmer credit repayment ability. The system is configured to calculate farm credit risk score based on the farm capability, farmer socioeconomic traits and entrepreneurial quality which helps to assess credit worthiness of farmer accurately. The credit worthiness of the farmer is analyzed using satellite data, field data from the farm and risks associated with them. The farm credit risk score is calculated in real time basis to every farm loan sanctioned by the lending institutions to safeguard their loss and non-performing loans.

Abstract: Monitoring of animals in a herd has various challenges. A method and a system for monitoring and measuring the behavior of a plurality of animals in a herd chamber is provided. The disclosure provides a method to develop a model to identify the animal interactions between a given set of herds of two or more animals. The system uses image, RFID sensors, animal phenotyping information such as species, breed, age and reproduction cycle information to generate an animal profile. This profile is used to quantify the interaction into an aggression score to the animals in the given herd. The aggression score over a given duration can help herd manager to put the animals with similar aggression score together. This will also help analyze the temporal aspects of the aggression score for a given animal and take preventive measures.

Abstract: State of the art systems used for monitoring of land (for example, agricultural land), fail to accurately assess various conditions in the land area and make predictions. The disclosure herein generally relates to agricultural systems, and, more particularly, to a method and system for micro-climate management in a land area being monitored. The system groups the different plots based on sensor trend information and based on a determined homogeneity information. A micro-climate view of the land area is accordingly generated, which in turn is used to generate micro-climate predictions.

Abstract: Crop loss estimation allows a user to monitor and estimate damage to the crops due to various natural events/factors. State of the art systems used for the crop loss estimation have the disadvantage that they do not convey to the users extent of damage. In addition to this, the existing methods do not take into account the recovery factor of the crops due to multiple factors and end up in overestimating the loss. The disclosure herein generally relates to crop monitoring, and, more particularly, to a method and system for crop loss estimation. In this method, crop loss is assessed based on real-time weather parameters and remote sensing data collected and processed, and crops are classified as being in one of a repairable damage class and a permanent damage class. The system also quantifies the crop loss, which allows the user to understand magnitude of the crop loss.

Abstract: A processor implemented method of detecting a concentration of plurality of chemical residue in an agricultural produce is provided. The method include (a) receiving, by a hyper spectral device, a data set associated with one or more reflectance measurements of the agricultural produce; (b) determining, data associated with a plurality of bands; (c) dynamically reiterating, the steps (a) and (b) at predetermined time interval to obtain a trained dataset; (d) determining, relevant wavelengths among the selected trained data sets based on a feature selection technique to form an array of emitters; (e) calibrating, by the identified array of emitters, to emit light on the detecting region of one or more sample of the agricultural produce to obtain data associated with reflectance and transmittance; and (f) calculating, a calibration index with a de-multiplication flag to detect presence or absence of the plurality of chemical residue in the agricultural produce.