SAWiE provides a site-specific mapping of smaller agricultural fields, crop vegetation, classification, yield, and health monitoring with the help of Automatic field boundary detection and implication of clean satellite image pixels. Which is then exploited for the extraction of crop-specific reliable spectral signature-based quantitative information for precise agronomic decision making.
SAWiE intelligent devices and spatial images work together, Enabling farmers to monitor their crop health for early detection and locate geo-specific anomalies, pests, diseases, and any other deficiencies. Hence allowing to deploy informed decisions about sowing sites vulnerable to yield losses, pests and quickly reacting to emerging problems of soil health along with the optimized scouting, soil maintenance, and irrigation.
Continuous analysis of crops with the help of satellites enables farmers to distinguish growing crops from the weekend and unhealthier ones. Hence using SAWiE tools plant growth stages will be examined with the help of multispectral images, this insight into plant count, canopy cover, and field potential allow farmers to apply inputs at the appropriate stage precisely within the field i.e distribution of drainage and irrigation systems and selection of optimum time to apply fertilizers, fungicides, and pesticide tracks plant growth throughout the season for better prediction of the crop output.
Satellite imagery and SAWiE data tools provide distinct changes in vegetation and growth attributes allowing Analyses of various cultivars and adopting the most productive one with the right quantity and time for seeding. This allows farmers to choose fields where they need to invest their time and resources
This includes the advisory tools that provide soil mapping, scouting, irrigation scheduling, fertilization/nutrient management plan. This helps the farmers to plan their input application to fields that need the most appropriate application. Comparative review of historical data in a particular retrospective provides the right choices of crop sowing for particular soil composition, intercropping rotation for production of higher yield and soil fertility.
We provide complete oversight of crops from seeding to harvesting ensuring growth factors mainly nutrients, air and soil quality, with greater precision, coverage. The predictive analytics can forecast anomaly propagation in the surrounding provides information for harvesting and disintegrates healthy crops from unhealthy ones. The survey helps to investigate infestation levels, trends, action thresholds and Issues early weather forecasts to take preventative measures, prepare for harvesting, manage labour and machinery. Also avoid any unforeseen events.
Using SAWiE tools, horticulture integrates with Remote sensing, AI, IoT and data science, crop heath and food safety is bringing agriculture into the pace of reducing GHG (Greenhouse Gases) emission. Remote sensing provides unique insight to the soil carbon store and soil health, while canopy coverage, yield mapping and spatial monitoring of fields. Which in return helps SAWiE farmers in reducing crop tillage, maintenance of diverse nutrients into the soil, minimizing soil erosion, steps to make soil resilient by crop cover and crop biodiversity. All these data-driven practices ultimately produce verified carbon credits.
SAWiE tools offer farmers environmental friendly, innovative and scalable agronomic solutions certified with USDA and EU. Geospatial analysis, crop growth modelling and soil analysis give clearer performance insights hence, enable farmers to implement more sustainable approaches. The overuse of pesticides leads to a damaging environment and a higher risk of pesticide residues in the food supply chain.
We offer specific benchmarks related to the farm analysis, crop properties, crop yield and tendencies to empower farming business. For this, geographical analysis of farms, agricultural and soil spectrums, crop monitoring is carried out. SAWiE technologies drones, satellite imagery, sensors and artificial intelligence allow farmers to analyze the quality of applied interventions and early cautionary measures define which of them work more efficiently. Along with predictive analytics, comparison analysis with other farms yields and methodologies are expected to boost up the yield hence, strengthen farmers.
