3 D Sensing
3 D sensing is a depth sensing technology that augments camera capabilities for facial and object recognition in augmented reality , gaming , autonomous driving and a wide range of applications. One way to sense 3D is using structured light coherent infrared light is transmitted onto an object with structured pattern . The reflected light can be decoded to construct a 3D image .
We are using 3 D Sensing to benefit the tribal people.
- It helps in Characterization of welfare habitats using 3D sources of data.
- Tribal people can be protected from wild species and vice versa.
- Advancement in modeling , prediction and exploration of forest wood and non wood forest products.
- Tribal people will have in depth knowledge about the product of forest .
- This technique can help the government to implement and introduce new schemes for tribal people.
- 3D GIS is instant and effective solution for larger and remote location where manual survey is difficult .
- Various urban / rural planing department require 3 D GIS data like drainage/ sewerage.
- The technique will be helpful in educating the tribal children .
So 3D sensing application is critical in coming years , as they will help to make people’s life easier and they have safety component to them
Our organisation have IoT policy also, we also encouraged Smart Agriculture, which includes the monitoring of soil moisture, vibrations, earth density, and pests, to detect potentially problematic patterns in land conditions and create a real-time monitoring system for Indian farmers. There exists in India a mechanism to avail real-time updates on farm’s soil conditions including soil moisture, PH levels, and nutrients, which then advises the farmers on pesticides and fertilisers, it has already been adopted by some large-scale farmers.
We are also working towards the adoption of drones for crop monitoring and spraying pesticides and fertilisers on crops, as well as web-based crop modelling, in an effort to promote agri-tech in the Tribals.
Smart irrigation system
Automated Irrigation System using WSN and GPRS Module Automated Irrigation system using WSN and GPRS Module having main goal is that optimize use of water for agriculture crops. This system is composed of distributed wireless sensor network with soil moisture and temperature sensor in WSN. Gateway units are used to transfer data from sensor unit to base station, send command to actuator for irrigation control and manage data of sensor unit. Algorithm used in system for controlling water quantity as per requirement and condition of filed. It is programmed in microcontroller and it sends command through actuator to control water quantity through valve unit. Whole system is powered by photovoltaic panels. Communication is duplex take place through cellular network. Web application manage the irrigation through continuous monitoring and irrigation scheduling programming. It can be done through web pages.
Crop Monitoring System based on WSN The subsequent section introduces the Bluetooth technology. Wireless Sensor network crop monitoring application is useful to farmer for precision agriculture. The application monitors the whole farm from remote location using Internet Of Things (IOT). Application works on sensor netowrk and two types of nodes. Energy saving algorithm is used in node to save energy. Tree based protocol is used for data collection from node to base station. System having two nodes one node that collect all environmental and soil parameter value and the other consist of camera to capture images and monitor crops. In this System Environmental changes are not considered for sensor reading. System user is not able to program application. There is no controlling system for application.
Automatic Drip Irrigation System using WSN and Data Mining Algorithm Data mining algorithm are used to take decisions on drip irrigation system. Automated drip irrigation system having WSN placed in all over farm and different type of sensors. WSN uses ad hoc network which gives self configuration and flexibility. Sensor data is given to base station and data is received using zigbee. Data processing is done at base station for decision making. Data mining algorithm is used to take decision on data from sensor to drip. All observation are remotely monitor through web application. This system works on Naïve Bayes algorithm for irrigation control. Algorithm works on previous data set for decision making if any attribute is not frequent result is zero.
Arduino Microcontroller Arduino is an open-source electronics platform based on easy-touse hardware and software. Arduino boards are able to read inputs – light on a sensor, a finger on a button – and turn it into an output – activating a motor, turning on an LED. A microcontroller is a small computer on a single integrated circuit. In modern terminology, it is a system on a chip. It contains one or more CPUs along with memory and programmable input / output peripherals. Microcontrollers are designed for embedded application. There are used in automatically controlled products and devices, such as automobile engine control systems, implantable medical devices, remote controls, office machines and other embedded systems.
While using GIS software, farmers are able to map current and future changes in precipitation, temperature, crop yields, plant health, and so on. It also enables the use of GPS-based applications in-line with smart machinery to optimize fertilizer and pesticide application; given that farmers don’t have to treat the entire field, but only deal with certain areas, they are able to achieve conservation of money, effort, and time.
Another great benefit of GIS-based agriculture is the application of satellites and drones to collect valuable data on vegetation, soil conditions, weather, and terrain from a bird’s-eye view. Such data significantly improves the accuracy of decision-making.
The sensors are able to give imagery in various spectra, allowing for the application of numerous spectral indices, such as the Normalized Difference Vegetation Index (NDVI). NDVI allows for the detection of vegetation content, the amount of wilting plants, and overall plant health. Next is the Canopy Chlorophyll Content Index (CCCI) that helps with nutrient application. Then, the Normalized Difference RedEdge (NDRE) detects Nitrogen content. And lastly, the Modified Soil-Adjusted Vegetation Index (MSAVI) is designed to minimize soil background impact at the earliest developmental stages of plants; the list goes on.
To simplify field observation, EOS has designed Crop Monitoring – a digital Platform that employs satellite monitoring in order to speed up a farmer’s decision-making so that he does not miss a crucial point of field treatment. Here are some of the features available in the platform:
Crop Monitoring allows the use of the Normalized Difference Vegetation Index (NDVI) for tracking crop health. This index monitors the amount of chlorophyll in plants which makes it possible to obtain information about their condition. When you have higher NDVI values, you have healthier vegetation, since the more chlorophyll available to the plant, the healthier it is.
Another important feature of Crop Monitoring is a Scouting app. It is both a mobile and desktop app that employs digital field maps. While using this app, a farmer is able to assign multiple tasks to scouts in few clicks. Add a field, drop a pin, set a task. Once the task is assigned, a scout moves directly to the selected location and checks problem areas at the site, inspects pest activity, performs weed management activities etc., immediately making records in the app. This allows inspection of the problem areas only when needed, thereby saving ample time to take necessary preventative actions.
Weather analytics. By analyzing weather data in-line with the data on plant condition obtained from satellite imagery, farmers can precisely apply irrigation and prevent frost or heat damage. For example, one of the best methods to avoid drought issues is drip irrigation with automatic or manual valve control, thus the farmer can apply the required amount of water to dry areas.
The strongest benefit of Crop Monitoring is the fact that it is based on satellite imagery. It helps to analyze field conditions or the state of specific areas and extract valuable information on-the-fly, thereby speeding up optimal reaction time as well as making reliable decisions – what crops to plant, when to harvest, how to effectively plan for the next season, what amount of nutrients and fertilizers apply, and many more.