Agriculture is undergoing a major transformation with the integration of advanced technologies that are helping farmers work smarter and increase productivity. The adoption of smart farming techniques and precision agricultural equipment is paving the way for more sustainable and efficient food production.
Enabling Data-driven Insights
One of the key aspects of smart agriculture is leveraging data analytics and sensors to gain valuable insights into crops and soil conditions. Farmers these days deploy a variety of sensors such as moisture sensors, temperature sensors, cameras etc. to remotely monitor fields. These sensors transmit real-time data to cloud or web-based platforms where it is analyzed using machine learning and predictive algorithms.
The data-driven insights help farmers understand patterns over time to take preventive actions. For example, moisture sensors can alert farmers about dry patches so they can irrigate targeted areas. This eliminates water wastage and reduces costs. Thermal cameras are useful in detecting plant diseases at an early stage for timely treatment. Overall, the use of IoT technologies for digitizing farms enables fact-based decision making.
Precision Farming Tools and Techniques
With precision agriculture, inputs like water, fertilizers and pesticides are applied only where and when needed saving huge amounts of resources. Variable rate technology (VRT) allows farmers to selectively distribute inputs based on soil composition maps. For fertilizer application, VRT systems integrate with GPS and GIS maps to adjust distribution rates across a field in real-time.
Similarly, drone and GPS-guided irrigation systems can target water delivery to parched areas of the field. Autonomous tractors using computer vision and AI are also being tested which can identify and remove weeds without harming crops. All these precision tools help optimize resource usage reducing environmental impact and operational costs.
Robotics and Automation Boost Efficiency
Labor shortages have led many farms to automate routine tasks and operations. Robots are increasingly being deployed for tasks like harvesting, pruning, manure scattering etc. Venture-backed startups are developing advanced agricultural robots that use computer vision, sensors and machine learning for autonomous operation.
Harvesting robots use computer vision systems to identify ripe fruits and vegetables and pick them precisely without damage. Their precision and consistency eliminate losses due to human errors. Automated tray harvesters are now common in berry farms. For pruning and propagation activities, robot arms fitted with sensors and tools can replicate the dexterity of humans.
Fully autonomous agricultural vehicles are also under development. They can plow, seed, fertilize and spray large tracts of land without any human oversight. This level of automation promises to boost productivity multifold by allowing round-the-clock operations. Drones are also an important tool for monitoring crops, detecting issues, and support decision making.
Optimizing Greenhouse Farming
Greenhouses allow farming in controlled conditions year-round even in unfavorable climates. Smart sensors and controls can help optimize greenhouse operations by automating critical parameters like temperature, humidity, carbon dioxide levels, irrigation and lighting. Computerized environmental control systems automatically manipulate ventilation, curtains and other equipment based on sensor feedback.
Precision horticulture techniques like hydroponics and aeroponics optimize water and nutrient delivery directly to plant roots. LED grow lights programmed with spectral recipes ensure optimal light spectrum for each crop growth phase. All these techniques help boost yields significantly while minimizing resource usage. Sensor-driven automation also ensures uniform growing conditions sustaining quality and consistency in produce.
Enabling Connected Community Agriculture
Technology Smart Agriculture Solutions is also being used to build connected communities and smarter models of community agriculture. For example, urban farming startups are promoting vertical community farms using hydroponics towers optimized for small spaces. IoT-based solutions allow residents to remotely monitor crop growth and environmental conditions. The harvest is then distributed locally or sold to generate income.
Crowdfunding platforms help gather capital for community agriculture projects bringing more land under sustainable cultivation. Shared resources like equipment, technical skills, and market linkages optimize the overall model. Technology has huge potential to strengthen connections between farmers and consumers as well as promote collective models of decentralized agriculture.
The Road Ahead
Advancing technologies hold great promise to revolutionize agriculture and ensure global food security in a sustainable way. As costs reduce and reliability improves, adoption of smart agriculture systems will accelerate. Advancements in robotics, autonomous systems, artificial intelligence, computer vision and precision tools will continue to optimize operations while reducing dependency on labor. Real-time analytics of huge volumes of agronomic data will power highly personalized precision farming.
However, challenges remain around data governance, cybersecurity, regulatory policies and access divide. Overcoming these challenges through collaborative efforts among industry, academia and policymakers will be crucial to realize the vision of an efficient, inclusive and resilient smart agriculture system for the future. With sustainable practice and the right enabling conditions, smart farming can certainly enhance livelihoods while nourishing people and the planet.
For more Insights, Read –
https://www.newswirestats.com/smart-agriculture-solutions-size-and-share-analysis/
Sensor Data Analytics Market, By Components (Hardware, Software), By Services (Managed, Professional), By Applications (Manufacturing, Healthcare, Automotive, BFSI, Telecommunication) - Forecast 2016-2022Sensor Data Analytics MarketThe global Sensor Data Analytics market is growing with the rapid pace is mainly due increasing adoption of Big Data analytics, which is propelling the Sensor Data Analytics market growth to the large extent.
According to a recent study report published by the Market Research Future, The global market of sensor data analytics is booming and expected to gain prominence over the forecast period.
The increasing demand of visualize real-time sensor data, are propelling the sensor data analytics market growth in the forthcoming years.
The failure in machine in manufacturing which are hampering the growth of sensor data analytics market.Access Complete Report @ Sensor Data Analytics Market Research Report-Global Forecast 2022Sensor Data Analytics Market, By Components (Hardware, Software), By Services (Managed,…Read on marketresearchfuture.comIndustry NewsSeptember 27, 2017 - Cloudera, Inc., a platform for machine learning and analytics optimized for the cloud, has introduced Altus data engineering for Microsoft azure beta enabling new hybrid and multi-cloud data analytic workflows.
This will help the data engineers use on-demand cloud infrastructure.July 11, 2017 - SAP SE has launched its new internet of things solution.
This includes IoT solutions that can take an advantage of advances in Big Data and analytics.
The growth sectors of the Sensor Data Analytics Market are identified with precision for a better growth perspective.Sensor Data Analytics, a statistical tool developed to collect and analyze the real-time data generated by a wired or wireless sensor.
The primary goal of sensor data analytics is to detect irregularities and these real-time data can later be used for various applications such as to detect failure in a machine in manufacturing unit or to get the data collected by drones to safeguard the businesses from various aerial threats posed by other malicious drones, to improve energy management to reduce carbon footprint of a facility or to cut queues and flight delays at the airports and so on.
As technology is growing, the big data have increased substantially, promoting the demand for data analysis for competitive advantage.
This has resulted in a huge amount of data stored by an enterprise, prompting the immediate need for data analytics.
Acknowledging the exponential growth, the market perceives currently; Market Research Future (MRFR) in its recently published study report asserts that the global sensor data analytics market is estimated to witness an outstanding growth by 2022, in terms of value, registering a stunning CAGR throughout the forecast period (2016 – 2022).Augmenting demand to counter the big data challenges that are increasing with the advancements of technologies are some of the key forces acting as a tailwind to the market growth, boosting the demand for sensor data analytics.
Additional factors substantiating the market growth include cost reductions from cloud deployment models, benefits of sensor data analytics, and the increasing need to address vertical specific challenges.
To begin with, the ones that will be in charge of social affair and following information, for example, the sensors, and, second, the gadgets that will play out some errand dependent on what information gets read, for example, cautions, locks, and valve actuators.
Since the information caught by sensors is delicate as a rule, Blockchain will enable clients to pick up trust in the IoT item advancement organization that brings Blockchain into the image.
Here's the means by which associations are utilizing the consolidated intensity of the IoT and Big Data:
Endeavors catch humongous information relating to their items/administrations/clients, in this manner improving their basic leadership keeping information at the central of basic choices.
Associations will settle on continuous choices about their coordinations, valuing, deals, and so on when they get exact data forms into significant bits of knowledge.
Along these lines, this conveys us to the worry of bestowing insight to machines with the goal that they know when certain parameters have moved.
