We promote IoTs and carbon free methods in digitalizing farming and aquaculture industry
6S-SMART FARMING METHOD
REVENUE EVENTUALLY INCREASE
RIS IS experienced in deploying Technologies and IoTs to transform agriculture in many aspects. We called it the 6s - SMART FARMING by deploying data analytics, communications and sensors technology, to improve productivity in farming
Data INCREASE
Data, tons of data, collected by smart agriculture sensors. weather conditions, soil quality, crop’s growth progress or cattle’s health. This data can be used to track the state of your business in general as well as staff performance, equipment efficiency, etc.
Control INCREASE
Better control over the internal processes and, as a result, lower production risks. The ability to foresee the output of your production allows you to plan for better product distribution. If you know exactly how much crops you are going to harvest, you can make sure your product won’t lie around unsold.
Cost & Waste REDUCE
Cost management and waste reduction thanks to the increased control over the production. Being able to see any anomalies in the crop growth or livestock health, you will be able to mitigate the risks of losing your yield.
Footprint REDUCE
Reduced environmental footprint. Automation also carries environmental benefits. Smart farming technologies can cut down on the use of pesticides and fertilizer by offering more precis coverage, and thus, reduce greenhouse gas emissions.
Product ENCHANCE
Enhanced product quality and volumes. Achieve better control over the production process and maintain higher standards of crop quality and growth capacity through automation.
Efficiency ENCHANCE
Increased business efficiency through process automation. By using smart devices, you can automate multiple processes across your production cycle, e.g. irrigation, fertilizing, or pest control.
Edge Computing for Intelligent Aquaculture
Aquaculture is similar to agriculture, except that instead of domestic animals, it breeds and harvests fish, shellfish, algae and other organisms that live in a variety of salt or freshwater environments. These environments can be very fragile; therefore, it requires high precision to create and sustain healthy and balanced ecosystems. To increase production while providing a safe and healthy environment for the animals, automation is highly desirable. This use case is also a great example of where equipment is deployed and running in poor environmental conditions.
This section describes shrimp farms, which are controlled ecosystems where humans and automated tools oversee the entire lifecycle of the animals from the larva phase to the fully grown harvestable stage. The systems even follow the transportation of the shrimp after they are harvested. Like agriculture, the environmental conditions highly affect the animals’ conditions, and therefore the ponds need to be closely monitored for any changes that might affect the well-being of the shrimp, so that prompt actions can be taken to avoid loss.
The architecture diagram above shows a detailed view of the edge data center with an automated system used to operate a shrimp farm.
Some of the system functions and elements that need to be taken into consideration include:
- Environmental monitoring, including data collection and reporting of metrics such as: outdoor temperature and humidity, water quality, PH value and temperature, dissolved oxygen, ammonia, nitrogen, and nitrite
- Video surveillance for illegal intrusion detection and compliance identification of staff using clothing and face recognition
- Smart breeding that includes automated feeding and inventory tracking (food, medicine, auxiliary materials, disinfectant and so forth)
- Platform traceability to query and display the entire supply chain to ensure high quality of aquatic products
By automating and connecting these farms, the solution minimizes the isolation that exists in this industry. The platform provides data to be collected and analyzed both locally on the farms and centrally to improve the environmental conditions and prevent mistakes while using chemicals like auxiliary materials and disinfectants.
With more computational power at the edge data centers, it is possible to store and analyze local monitoring data for faster reaction time to manage changes in environmental conditions or modify feeding strategy. The system can also pre-filter data before sending it to the central cloud for further processing. For instance, the system can pre-process water quality data from the monitoring sensors and send structured information back to the central cloud. The local node can provide much faster feedback compared to performing all operations in the central cloud and sending instructions back to the edge data centers.
Digitalization has already provided much innovation, but there is still room for improvement, such as reducing the labor costs related to collecting data and improving data analysis to be faster and more reliable. With edge computing techniques, it is possible to build intelligent aquaculture infrastructure in order to introduce artificial intelligence and machine learning techniques that will optimize feeding strategy or reduce cost by minimizing human error and reacting faster to machine failures.
INTELLIGENT AQUACULTURE
With edge computing techniques, it is possible to build intelligent aquaculture infrastructure in order to introduce artificial intelligence and machine learning techniques that will optimize feeding strategy or reduce cost by minimizing human error and reacting faster to machine failures.
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