Kateryna describes how remote monitoring using satellites is revolutionizing how farmers combat crop infestations and diseases through the analysis of high-resolution images and advanced data analytics. I’ll let her explain the rest. As always your comments are welcomed.
Pest and disease management is crucial in agriculture, protecting crops from seen and unseen threats that devastate harvests and livelihoods. Traditionally, farmers have relied on their experience and natural remedies. Today, geospatial data availability and analytics have transformed agricultural practices using tools like satellite imagery, drones, and a form of artificial intelligence called machine learning to detect pest and disease crop infestations allowing for early and precise interventions. Tools include smart sensors deployed to monitor soil and plant health in real time and data analytics to offer insights into effective pest control. Biotechnological advances using genetic modifications are producing disease-resistant crops and reducing the need for chemical pesticides.
Although satellites may seem far away and incapable of spotting something as small as an insect, other pests and early stages of disease, they are proving to be quite effective in these tasks.
Two technological advances, one an Earth observation instrument and the second, EOS Data Analytics when combined represent the current state-of-the-art to help farms monitor different crop and soil parameters from advanced remote satellite imaging and data collection.
Traditional methods while rooted in time-honoured wisdom and experience face many limitations and challenges in today’s complex agricultural landscape.
One of the primary issues is the unpredictability of pest and disease outbreaks. Growers often rely on manual inspections and past experiences, which can be subjective and inconsistent. This reactive approach means that infestations are often identified only after they have caused damage that is already impossible to avert completely.
Another limitation is the reliance on chemical inputs. Although they can be beneficial in the short term, these substances cause detrimental effects on the environment, including soil degradation, water contamination, and harm to beneficial insects and wildlife.
Another issue to consider is pest resistance to chemical treatments over time, which means even stronger hence more harmful analogues need to be applied with negative environmental consequences.
The labour-intensive nature of manual monitoring and intervention requires substantial time and effort which can be particularly burdensome for small-scale farm operations. Furthermore, these methods often lack precision and lead to the over-application or under-application of treatments.
Climate change also doesn’t work in our favour here. Warmer temperatures and changing precipitation patterns create better conditions for pests and diseases to thrive often in areas where previously they were of no concern.
Given these limitations, the need for innovative solutions becomes clear. Precision agriculture tools such as satellite imagery provide farms with real-time data and early warnings of potential threats. Machine learning and data analytics enable more accurate predictions and tailored interventions reducing reliance on chemicals.
Satellite technology with its far-reaching eyes offers growers a way to manage fields in ways that no other methods can. By analyzing high-resolution images farmers can see early indications of changes in vegetation patterns, colour and growth no matter the weather conditions and distance. The application of predictive analytics along with these images gives farmers the tools needed to make smart decisions.
Satellites identify signs of disease or pest outbreaks utilizing vegetation indices like NDVI, NDMI, ReCl, and NDRE. These track the state of health of plants at different stages of growth.
EOSDA Crop Monitoring from EOS Data Analytics leverages these indices to provide real-time insights into crop health. A crop monitoring system can assign scouting tasks to farmers based on satellite data. The system can confirm crop damage, identify specific diseases (biotic or abiotic), and communicate detailed descriptions to agronomists and farmers for timely interventions.
Using GPS coordinates a crop monitoring system can precisely target an area for intervention rather than address the problem as field-wide.
The predictive analytics in the Disease Risk feature of EOSDA Crop Monitoring spots nascent pest infestations and diseases before they become a larger problem. The analytics can assess risk levels across different zones allowing farmers to prioritize and address the most endangered crops.
A Data Manager feature provides data analysis comparisons to make accurate yield assessments during harvesting. It produces maps that highlight areas of varying productivity and can help identify and manage low-productivity plots resulting from biotic pathogens.
EOSDA Crop Monitoring also offers data on soil moisture levels, temperature extremes, and weather conditions to ensure that farmers can manage both biotic and abiotic factors to safeguard their yields.
Using real-time remote sensing data gives farmers the means to make smarter decisions when using pesticides to target affected crops. Detailed satellite imagery can identify exactly where these infestations are happening allowing for precision rather than blanket application of chemicals and pesticides. Cutting down on chemical and pesticide use lowers costs and reduces environmental risk.
Satellite tracking of soil health and moisture levels means farmers can use less of both more effectively ensuring these resources get applied where needed most to promote sustainable farming practices.
Expect satellite technology to continue to play a critical role in precision agriculture. Biotechnological innovation is also paving the way for safer pest control methods. A good example is the Wolbachia project which breeds mosquitoes that can’t transmit diseases. We are already seeing the use of biological weather stations to identify and track pest species and diseases providing valuable data to predict and manage outbreaks. At the same as in the Wolbachia project, we are using the science of genetic modification to deal with these invasive threats.
The Internet of Things is being deployed today to support agriculture. It is revolutionizing pest monitoring using millions of sensors to collect environmental, optical, and sound data. This real-time information enables early detection and facilitates targeted interventions.
Big Data analytics combine information from various sources including pest biology, weather patterns, and control activities to optimize strategies and provide holistic insights into pest dynamics. AI is enhancing analytics tools by adding the capacity to offer recommendations or even apply autonomous decision-making to a perceived threat.
Robotics and drones are bringing precision to pest management enabling their detection and control regardless of location. Drones and field robots can precisely target the use of pesticides or biological agents minimizing chemical use and environmental harm, and they are only getting more sophisticated and smarter.
Augmented reality and virtual reality are playing a part as well. Virtual reality can be used to train farmers. Augmented reality can give farmers a heads-up view of all the data and imaging information to help make decisions about where the problems lie and best practice solutions.
All of these advancements are creating more sustainable, efficient, and resilient agricultural practices that can meet the challenges of pest and disease management here in the 21st century.
]]>Founded by Mike Prorock, the owner of a farm in Chapel Hill, North Carolina, The Earthstream Platform was his way to help him with his business. Using a number of wireless, solar-powered sensors, tied into a hub with an application interface (see image below), Earthstream can see local condition details like soil moisture and temperature, measure light levels, track growing degree days, and more.
For farmers, ranchers, golf course and park managers, and other land parcel requirements, Earthstream assesses what is happening in the environment in real-time.
Earthstream gathers data from multiple sensors on the land and even data collected from drone overflights. It also tracks weather service information and fuses this with real-time local weather data to provide a local, accurate picture of the environment. Information is continuously updated providing automated alerts, detailed data analysis, and recommendations. It will tell you if you are using too much or too little war. It will tell you the health of your turf, your crops, your soil and subsoil depending on what package of sensors are in place on the property.
In a recent presentation at the United Nations, Mesur.io brought along a living garden to showcase Earthstream. It was an instant hit.
So why is what Mersur.io is doing so important?
On the website it uses these words
“Give the Earth a voice.”
It seems an appropriate phrase in the age of anthropogenic climate change, because how we interact with the planet will be the key to its and our survival.
In a recent report aired on CNN, we were told that humans are using 1.75 Earth-equivalents each year in terms of what we take from this planet. Knowing this, our ability to measure the planet’s health, and biodiversity for every hectare of land is critical. And being able to do it in micro-detail, means we can get more out of each hectare, and do it sustainably because we have the data measures for all that is necessary for sustainability.
So what started off as an individual farmer trying to manage a Chapel Hill farm has turned into a tool for all of humanity in our mission-critical task to maintain our planet and the life on it.
With a real picture of the planet’s cycles, “from germination to consumption,” it gives us the means to put the important numbers next to our practices and measure our progress.
]]>In 2019 there are many data analytics or business intelligence (BI) software tools available for organizations, with many coming from companies that have been traditional information technology powerhouses. A number of new startups, however, are emerging to give these “old boys” a run for their money. So Microsoft, IBM, Oracle, and SAP need to be looking in their rearview mirrors at the growing competition that offers in many cases free trials of software in a “try before you buy” strategy.
What does data analytics allow organizations to do? Mine the data they already have and the data they collect daily to create insights into how to improve their businesses. It means anyone working with data can become a problem solver by understanding what needs to be solved and finding the information already at his or her disposal.
The following briefly describes the newest movers and shakers in BI and data analytics and what they bring to the table. We call this group:
Data preparation, self-service, and data blending are three of the key competencies of Alteryx. One of the more commonly-used applications of the company is the software to clean data accessed from large data warehouses, spreadsheets, and the cloud. Alteryx provides a solution that is scalable and can be utilized on-premises or through the cloud. Its software is being used by financial services, healthcare providers, retail, logistics and transportation, oil and gas, and the public sector.
Birst provides a virtual BI presence that is interwoven with its clients’ actual data to rapidly unify different departments in an organization to produce useful insights and better data governance. Data from multiple database sources gets integrated quickly to create a single picture that can then be broken down to extract information and connect different pieces from on-premise or cloud sources to create the big picture.
If you are familiar with Google Analytics, then you can understand a little bit about what Clicktale does. Seen as Google Analytics key challenger, it uses behavioural analysis to create deep insights into key business activities. One such example is its path analysis, which in essence allows tracking of end-users’ paths to websites and what they do when on them.
Domo offers a real-time, holistic approach to data making an organization’s data sources accessible and useful for everyone within the business including partners and customers. Domo offers a mobile version compatible with both Android and iOS and comes with real-time alerts, drag-and-drop options, and interactive dashboards. It describes its offering in seven enterprise-scale systems for business decision making that include connecting, storing, preparing, visualizing, collaborating, predicting, and extending an organization’s data assets.
Looker specializes in data discovery and has the ability to connect to relational SQL-built databases in order to extract relevant data for business needs. It enables employees to access data, ask relevant questions, and have the data presented in a fashion utilizing terms familiar and relevant to individual departments bypassing the need to have a data analytics specialist on the payroll. States Deepak Bloor, a marketing blogger at Bigassignments and Oxessays, “This is an award-winning software solution and key components include advanced data scheduling and web integration.”
On its website, Oribi states, “Analytics is for analysts…Oribi is for everyone.” Described as another Google Analytics competitor, Oribi provides an array of analysis features to track information such as how existing and new users interact with the features of an organization’s website. It lets you know what is working and what is not. It tells you where your visitors arrive from, and what is driving their visit, providing behavioural analysis to help create high-level traffic and conversions from visitors to users or buyers.
Qlick is a long-established data analytics player most synonymously associated with its flagship Qlick Sense tool. The unique feature of this offering is its capability to round up all company data sources and deliver them in a single, easy-to-use dashboard. Qlick describes itself as providing users with a tool that allows them to get answers to the questions they ask, as well as explore the data to answer questions that have yet to come up. States Belinda Nightingale, a sales manager at Eliteassignmenthelp and Stateofwriting, “The associative engine uses in-memory to combine all of an organization’s library of data, ensuring that almost no stone is left unturned when a data search is run based on a query.”
Sisense is an API (application program interface) tool that allows users to mashup their data and create their own analytics applications which they can embed anywhere in the organization. It uses Elasticubes, customizable data structures for data visualization, analysis, and dashboards. Its ecosystem is built upon multiple statistical tools which include regressions, correlation, and variance. There are also tools available as add-ons to upgrade and further customize dashboards depending on business needs.
Tableau provides an offering that allows companies to collect data from multiple sources including Cloud Apps, Google Analytics, CRM (customer relationship management) tools like Salesforce, spreadsheets, SaaS, and SQL-style databases. Tableau focuses on creating a narrative story for all the data it collects, displaying it through interactive visualizations on a dashboard accessible by all departments, and by key business verticals in numerous industries. Available on-premises, or hosted in the cloud, Tableau includes mobile versions compatible with both Android and iOS systems.
Use Yellowfin for Machine Learning Capabilities
If your objective is to allow key stakeholders to better understand the data your organization collects, then YellowFin is a great solution. The company was founded in 2003. Its end focus is knowledge that can be acted upon. It uses a host of features including machine learning. It is predictive to help with business strategy. And finally, it is fully integrated to allow for a host of data visualization options and includes customizable alerts configurable for select users.
And here are the offerings from the established information technology companies when it comes to BI and data analytics. We call this group:
IBM unsurprisingly offers a comprehensive range of data analytics and BI tools, which can be broadly separated into two distinct solutions. Cognos Analytics is all about self-service and automation to create dashboards and reports, while Watson provides artificial intelligence (AI) to produce smart discovery data, which in effect allows users to collect data for analysis without the need for a data analytics specialist. It’s advanced data governance tools make perfect sense for deployment in large organizations where different employees are given different levels of access.
Microsoft offers Power BI, a cloud-based data analytics tool. Truly multi-faceted, it combines self-service, integration and cloud-computing capabilities. Described by Microsoft as a business analytics service, it delivers insights to enable fast, informed decisions by transforming data into stunning visuals which can be shared on any device, a visual means of exploring and analyzing data, collaboration on shared, and customizable dashboards with interactive reports. Power BI can scale across any size organization and provides both built-in governance and security.
Established industry player Oracle offers two solutions: Business Intelligence 12c and Oracle Data Visualization. The former offers a more fundamental style of analytical tools. The latter provides a set of user-friendly applications such as drag-and-drop and familial graphs and other visual statistical tools. Oracle’s data discovery capabilities makes it suitable for big businesses operating in global markets.
This SAP Business Intelligence Platform is available on the cloud or in-premises and specializes in gathering actionable data. With user-focused dashboards and data visualization tools, it offers a self-service solution and is an industry leader in providing easy-to-understand business data upon which to act for relevant departments and employees.
An impressive aspect of these BI and data analytics tools is their ability to end the need for many companies to hire specialists in the field. In bigger organizations, these are positions that add tremendous value but only where the budget allows for their hire. Smaller businesses often ask other employees to perform data analytics even though this is not an area of their expertise.
Fortunately, with these new software offerings providing incredible functionality, data and business intelligence analysis can now become something that is increasingly undertaken by non-experts and key stakeholders, allowing for an element of oversight of data which was previously unthinkable.
The tools are evolving and moving businesses into a new realm of data analysis with increasingly advanced options that are incorporating developments in AI and machine learning.
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