SENSEACRE

Sensors are key to any project outcomes.

Senseacre team has expertise in sensor fusion and based on the industry requirement we integrate the relevant sensors as below.

We use a combination of RGB, Multispectral, Hyperspectral and Thermal for best outcomes.

Established and mastered the framework of capture, stitch, process, analyze of UAV imagery.

Senseacre would automate this using deep learning on proprietary algorithms and data sets.

Automated detection of Diseases, Insects, Weeds Nutrient deficiencies and abiotic stress.

Currently co development with pentagram research in building machine learning algorithms for specific use cases in the able guidance of Dr E G Rajan a knowledge bank in image and video analytics.

To identify and detect color based and shape based feature extraction.

The ability to measure actual photosynthetic activity is a breakthrough made possible with Senseacre identifying the high-resolution fluorescence imager that is the smallest and lightest of its type.

This instrument has a spectral resolution of between 0.1 and 0.2nm, allowing it to capture very weak Oxygen A-B bands where indications of vegetation stress exist.

Chlorophyll levels, leaf optical properties and vegetation structures can thus be determined rapidly and in near real-time with this Solar-Induced Fluorescence imager.

Senseacre partners with global best for above sensor integration.

Senseacre weed detection is to identify the percentage and the exact location of weed-infested areas on your field. And to turn your field’s data into relevant and action able information, weed analyses are always conducted in close collaboration with professional agronomists.

To get conclusive results, it’s important to upload high-resolution images. Having high-quality images allows us to provide you with results that go beyond the mere analyses of differences in color. Additionally, Senseacre Weed Analyses provide you with the exact georeferenced positions of the identified weeds.

   Spot weed-infested areas in time and before they affect your current yield goal.

   Optimize weed control measures by applying the right amount of herbicide on the right spots.

   Identify the precise location of weed-infested areas for more effective treatments.

   Fast and save time and resources.

   Able to cover more than100 acres in an hour.

   Accurate – with drones, you are able to analyze every inch of your field.

   Proactive and allow effective in-season corrective measures.

Our research with Multispectral and Hyperspectral imagery on crop has given us clear indications on the possibilities of pest detection and classification across the crop area.

We are building algorithms in pest detection and classification using machine learning on Fall army worm and Pink boll worm currently.

Initial results have been very encouraging, and we are working on maize, cotton and rice crops for Rabi and Kharif and should have more results as we progress.

We should be able to give economic impact of using drones for early detection and quarantine of pests soon.

In construction activity, progress monitoring is a challenge. With drones that can be simplified with image and video evidence. We can capture and generate orthomosaics, 3D point clouds, build digital elevation models and contour maps, perform boundary and topographic surveys, develop as build drawings, measure distance and volumes, monitor site development progress.

The use of LiDAR and aerial data imagery on construction sites is an innovative approach that can identify better work practices, highlight safety issues and provide a new perspective to owners, contractors and investors. Frequently capturing reality data, overlaying plans and sharing with stakeholders helps project managers and superintendents stay on schedule and prevent cost overruns from expensive rework.

Our Data Analysis and Reporting enables construction managers to quickly and easily capture aerial imagery of a jobsite, gather site data with context, analyze real time data, and distribute it to relevant team members. Our team of expert engineers can generate maps, point clouds for 3D modeling, stockpile volume calculations and reports to effectively plan your construction projects and monitor site progress over time.

Using drones, drone imagery, and image data to support mining, quarry, or mineral production operations (such as volume calculations and grading compliance measurements) is increasingly touted as the safer, faster and more accurate data gathering approach.

Mineral production operations managers can then use such data to digitally map existing conditions and measure stockpile volumes for inventory management, production forecasts, and auditing.

UAV imagery plays an important role in the disaster management. It gives access to the sites on near real time and can assess the magnitude of the disaster in both video and image format.

Crop loss in the form of natural disaster. We can quickly fly and capture imagery and give crop loss assessment report covering crop area, crop sown, stage of crop and the impact of disaster.

Drones in Agriculture is the most emerging technology. Senseacre has expertise in Planning, Fly, Capture, Process, Analyze and Publish results as below in different formats.

Senseacre can do urban and smart city land map land use analysis using drone imagery.

We can trace every investment made in the development of the urban and smart cities periodically and deliver exception evidence for decision making and revenue generation.

Senseacre is an industry leader in stockpile measurement and inventory management to the mining and aggregate industries. We provide your company an unbiased third party measurement for inventory, valuation, overburden removal and key operational insights to manage your site.

Some of the outcomes are cliff and rock formations, site planning, keep track of mining equipment’s, contour maps and slope analysis.

Our nationwide presence and advanced data- driven LiDAR and Drone Aerial Data solutions allows us to better serve our customers unique site needs more efficiently and economically.

There is no Company with more experience in providing measurement services to the mining industry than Senseacre.

The Senseacre Data Analysis and Reporting allows users to validate and transform raw aerial data into dynamic 3D models and accurate and precise measurements. It offers powerful analytics and data driven insights in every part of the mining and aggregate production life cycle including exploration, planning/permitting, operations, and reclamation.

We provide your team with survey-grade data to accurately and effectively perform pit progression scanning, reserve calculations, blast volume calculations, settling pond airspace calculations and other mine operations.

Construction monitoring of dams is very herculean task. Drones can make easy access to the site irrespective of the terrain and extent. You get amazing clarity images and videos to access and monitor the progress. The same images can be integrated to ESRIArcGis, BIM or any third party software for progress comparison.

Insurance and Disaster management Images don’t lie.

Using Drones to capture images and videos for fast and accurate evidence for crop loss assessment is a game changer in the industry.

Farmers, claimants, insurance companies and government can have uniform access to data for calculation of crop area, crop, what state the damage has occurred and the extent of the damage.

This is easily integrate to economic indicator and can be disbursed.

Prof. Dr. E. G. Rajan B.Sc., D.M.I.T., M.E., PhD, FIE is the Founder President of the Pentagram Research Centre (P) Ltd., Hyderabad, India. He is an Electronics Engineer and a Professor of Signal Processing having about 42 years of experience in teaching, research and administration.

He has a number of publications to his credit. He has been a professional member of ACM and an editor of the journal of AMSE, Royal Academy of Doctors, Barcelona, Spain.

He received his Ph.D degree in Electrical Engineering, (Signal and Image Processing), from Indian Institute of Technology (IIT), Kanpur, U.P., M.E. degree in Applied Electronics, from Madras University, the then famous DMIT in Electronics Engineering from the Madras Institute of Technology, Chromepet, Madras and B.Sc degree in Physics from Madras University.

His contribution to the state-of-the-art of Electronic Warfare and Support Measures has been well recognized in the Government and industrial sectors. He was a noted teacher in the department of Electrical Engineering of the Indian Institute of Technology, Kanpur.

He received Distinguished Scientist and Man of the Millennium Award from Who is Who Bibliographical Records, Cambridge, 2000. He authored many books like, Symbolic Computing – Signal and Image Processing, Electronic Order of Battle Records of Military Radars, Computers and Information Technology and Foundations of Information Technology. He is the father of a novel paradigm Symbolic Computing In the Framework of Markov’s Constructive Mathematical Logic.

His contribution to Computer Vision, Pattern Recognition, Modeling and Simulation, Artificial Intelligence and Machine Learning Could be seen in his research publications. Two of his sixty five Ph.D scholars were involved in the design of digital circuits using organic molecules and some of them are working in the area of Big Data Analytics pertaining to Genome Data Base, Biometrics Data Base, Medical Data Bases like MRI and CT Scan imageries of Breast Cancer, Geospatial Data Bases like Multispectral Satellite imageries and Subsurface Three Dimensional Radargrams obtained using Ground Penetrating Radars.

He has brought out more than 25 original patentable concepts. One such concept is Codon Space, which advocates the theory of Life Forms as Subspaces of the Information Space called Codon Space. Another concept is a Mathematical Transform, which goes by his name as Rajan Transform.

On November 15, 2015, he was awarded the prestigious Dr APJ Abdul Kalam Gold Medal for his life time achievement in Teaching, Research, Industrial Development and Corporate Social Responsibility.