Smart Software Solutions & Mobile App Development: Current IT Trends in Agriculture
Innovative Mobile App Development and Today’s 3 Must-Have Solutions Available to Agritech Companies
This day mobile app development keeps transforming every modern industry, driven by progressively growing tech demand for process automation, coupled with greater productivity and high-quality personnel training. And agriculture is no exception. From the viewpoint of contemporary Agritech business, there are several primary driving forces found behind smart software and mobile app development. Taken in general, most of them are falling into remote monitoring, IoT, Big Data analysis, proactive decision-making, staff education, etc. This also includes the rest of innovative technologies that can benefit better ROI throughout more affordable labour cost, therefore providing agricultural businesses with critical competitive advantages, which are retained over time. So, when it comes to choosing the right highly specialized IT provider, it’s essential to understand what type of solutions can be basically derived from each innovative technology in that area. To get a clear picture of must-have expertise, which should be prioritized beyond all — this article is about to cover 3 core sectors of smart software and mobile app development in agriculture. Here they are.
Embedded IoT-based Software Applications: Precision Farming, Crop or Livestock Management
With the compound annual growth rate of about 13%, global market of smart agriculture driven with IoT technologies is expected to surpass $11.23 billion investment by 2022 already. It means that capitalizing on high-profile IoT, embedded software products and related custom applications can help farmers perform everyday tasks more efficiently — taking the right action and at extremely short notice. This group of solutions covers different field supervision works, such as crop scouting, livestock monitoring, and precision farming. Basic data tracking effort on air quality, soil, weather, crop maturity also rank among the most important mechanisms over there. Supporting effective indicative analysis based on Normalized Difference Vegetation Index, IoT applications and individually tailored software solutions are often used to set up cost-effective agricultural projects using:
- Data collection and information delivery centers, coupled with cloud computing technologies for more intelligent risk management.
- Ground-based sensor networks and smart drone-assistants for optimal maintenance, valuable insights, timely alerting & planning, which should be compatible with Android-based smartphones/tablets.
- Precision farming, sensing and pattern-recognition technologies that can provide maximum accurate data-driven evaluations and ultimate control over the whole manufacturing cycle.
Big Data Engineering for Smart Live Tracking, Enhanced Predictive Analysis & Supply Chain Management
Regarding its practical usage in software and mobile app development for Agritech businesses, big data engineering and smart analytics are commonly applied to process & store tons of live tracking data pulled together from various devices. Big data mechanisms in agriculture range from relatively simple systems of feedback or thermostat-like regulators, to algorithms and sensor machines of the highest complexity. Nevertheless, most of them are generally revolving around:
- Detailed score tracking and definitive statistics giving clearly visible in-field picture of multiple locations. Ultimately — to address potential emergency cases, and tackle sudden changes in the operational environment in a proactive manner. Precision farming driven by big data aggregation takes advantage of valuable insight regarding crop productivity or livestock well-being. And that results in enhanced decision making and more consistent maintenance over time.
- Predictive modeling available with extensive data aggregation on the overall soil conditions, expected weather or pest precautions, as well as advanced fertilizer requirements, irrigation or watering status, etc. Big data analysis also contributes to boosting feed efficiency in livestock growth, reducing crop failure ratio, and preventing product spoilage by getting certain perishable assets quickly moved to the right place.
- The basis of big data also unlocks myriads of uncovered opportunities for elevating supply chain efficiency throughout well-optimized processing, producing and distribution operations. To demonstrate its strong potential in food supply chain regulations, we can reasonably take on security tracking, live crop monitoring, as well as proactive planning for irrigation, nutrient application, or pest control efforts.
Machine Learning, In-Field Reporting and Innovative Education Programs for Workforce Training
Based on the recent survey, the global market of Agritech software with AI and machine learning is estimated to get the existing net worth of over $518 million amplified to $2.6 billion by 2025. Such significant growth in the industry is currently driven with factors like surging world’s demand for agricultural products, booming popularity of data management systems, as well as rapid tech developments for higher crop productivity. Therefore, combined with big data, Artificial Intelligence and innovative education programs for workforce training are now changing the industry with:
- Agricultural AI-based robots deployed for handling lots of essential industry-related tasks in precision farming, such as spraying herbicides with high accuracy to prevent resistance or, for example, harvesting crops at greater speed. Leveraging computer vision and AI for maximum precise monitoring and action taking, these in-field innovations contribute a lot to cost-effective manufacturing in Agritech business.
- Deep-learning algorithms and advanced date procession captured by drones, satellites, and other IoT-based devices. All can be easily pulled together within a single Android or IOS software application. Backed with image recognition function, such innovative solutions are beneficial to reportedly identify potential crop defects or nutrient soil deficiencies relying on sophisticated AI-based algorithms and big data frameworks. This area of development clearly demonstrates an incredible potential for data extraction and aggregation, combined with the right visualization tools and intelligent software products.
- As for innovative education programs for workforce training, here we can take Syngenta project for perfect example in mobile app development. Fostering the active development of collaboration and group-led skills in data-driven decision making, this individually tailored solution for agricultural staff training has proven efficiency — driving general workforce productivity to a certainly higher degree, besides in a really playful manner. That can facilitate more accurate analysis and reporting by agricultural workers, providing extensive practical knowledge and guidance. Ideally, high-quality mobile app development for workforce training in agriculture can allow employees perform analysis by soil type, region, cropping stage, and lots of other primary indicators — to quickly identify significant trends, potential opportunities, and current trends just as they occur.