CASE STUDY

The Farming Information Model

This case study shows how a blockchain-based information model can support the operations of an aquaculture farm. A salmon farmer equips his farm with the latest in sensor tech and uses a blockchain-based database to increase the internal efficiency of the farm’s growth process and gain a competitive advantage through complete availability of data.

Database

The database of the application receives data from various sources inside and outside the farm. External data includes upcoming weather conditions, storms, current market prices and the spread of diseases in surrounding aquaculture farms. Internal data is collected using IoT-sensors and smart devices. There is no human data input to prevent human failure or human manipulation. IoT-sensors enter the recorded data automatically and directly into the database without an intermediary. Once the data enters the blockchain database, it will be timestamped and can not be altered anymore. This secure and tamper-proof data-input lets the farmer rely fully on the model rather than running tests in the actual farm which saves time and money.

BIM supports the construction process in three steps:
1. Plan the project assessing internal and external factors. A complete simulation of the building is being created in advance for more detailed visualization and a thorough risk assessment. The capabilities of advanced data analytic sallow for various data inputs that may later affect the project in some way. Think of traffic data to precisely calculate the delivery of resources to the construction site or the analysis of weather data to avoid interruptions due to adverse weather-conditions.

2. Monitor ongoing processes of the construction site. Data input along the construction allows planners to constantly align the actual data with the data of the model and recognize deviations in real-time. Faster identification of mistakes and agility in adjusting of inefficiencies within the construction process are the result.

3. After finishing the production process there will be a complete database at hand. Including data about the entire production process and the execution of all steps of the production plan. This data can be used as a proof of work, a proof of sustainability, or to feed the BIM-systems for future projects.

Operational Planning

Visual sensors in the pools can precisely track the growth of the fish and determine the quality along the growing process. Water quality is constantly measured to identify impurities and diseases in the water. With this data at-hand, the application offers a continuously updated dataset to the operator that largely facilitates internal decision-making processes. This includes a real-time valuation of all assets inside the farm, growth data, health data, and market insights. It allows the operator to plan ahead better and learn from inefficiencies in previous production processes.

BIM supports the construction process in three steps:
1. Plan the project assessing internal and external factors. A complete simulation of the building is being created in advance for more detailed visualization and a thorough risk assessment. The capabilities of advanced data analytic sallow for various data inputs that may later affect the project in some way. Think of traffic data to precisely calculate the delivery of resources to the construction site or the analysis of weather data to avoid interruptions due to adverse weather-conditions.

2. Monitor ongoing processes of the construction site. Data input along the construction allows planners to constantly align the actual data with the data of the model and recognize deviations in real-time. Faster identification of mistakes and agility in adjusting of inefficiencies within the construction process are the result.

3. After finishing the production process there will be a complete database at hand. Including data about the entire production process and the execution of all steps of the production plan. This data can be used as a proof of work, a proof of sustainability, or to feed the BIM-systems for future projects.

Growth Process

At the very beginning of the growth process, the fish is tokenized . That means that a digital version of the salmon is being created inside database, all data is then linked to the individual product. Data collected along the growth process gives the farmer the opportunity to react to incidents quicker and gain an easy overview of the entire operation. Feeding schedules can be adjusted along the growth process, the optimum point of harvest can be determined better, and diseases can be treated faster. Data-based decision making can improve farming in many aspects.

BIM supports the construction process in three steps:
1. Plan the project assessing internal and external factors. A complete simulation of the building is being created in advance for more detailed visualization and a thorough risk assessment. The capabilities of advanced data analytic sallow for various data inputs that may later affect the project in some way. Think of traffic data to precisely calculate the delivery of resources to the construction site or the analysis of weather data to avoid interruptions due to adverse weather-conditions.

2. Monitor ongoing processes of the construction site. Data input along the construction allows planners to constantly align the actual data with the data of the model and recognize deviations in real-time. Faster identification of mistakes and agility in adjusting of inefficiencies within the construction process are the result.

3. After finishing the production process there will be a complete database at hand. Including data about the entire production process and the execution of all steps of the production plan. This data can be used as a proof of work, a proof of sustainability, or to feed the BIM-systems for future projects.

Making Data available to external stakeholders

All data related to the specific product is stored in a database along its growth process. This data can be used to prove product specifications. In a selling process, the farmer can verify the quality and origin of his products towards the wholesaler. Each time the salmon is being sold, the growth data can be used as an advantage in the selling process. Data includes a day-by-day record of the growth process and conditions, medication, diseases, and any other events along its production. This level of information depth gives the farmer a significant advantage in the selling process.

BIM supports the construction process in three steps:
1. Plan the project assessing internal and external factors. A complete simulation of the building is being created in advance for more detailed visualization and a thorough risk assessment. The capabilities of advanced data analytic sallow for various data inputs that may later affect the project in some way. Think of traffic data to precisely calculate the delivery of resources to the construction site or the analysis of weather data to avoid interruptions due to adverse weather-conditions.

2. Monitor ongoing processes of the construction site. Data input along the construction allows planners to constantly align the actual data with the data of the model and recognize deviations in real-time. Faster identification of mistakes and agility in adjusting of inefficiencies within the construction process are the result.

3. After finishing the production process there will be a complete database at hand. Including data about the entire production process and the execution of all steps of the production plan. This data can be used as a proof of work, a proof of sustainability, or to feed the BIM-systems for future projects.

Collecting Data Beyond the growth Process

Growth data ranges from the point of origin to the processing and packaging of the finished product. Sensors in the pool start transmitting data when the larvae are added to the pool and stops once they are taken out of the water. Data is linked to each individual product using tokenization. Once the product leaves the farm, there is more relevant data to be collected. The salmon is being frozen and transported to a wholesaler. The wholesaler will sell the product via different distribution channels. All related data regarding the transport, compliance to the cold chain, and appropriate handling of the goods are linked to each individual product on the blockchain database.

BIM supports the construction process in three steps:
1. Plan the project assessing internal and external factors. A complete simulation of the building is being created in advance for more detailed visualization and a thorough risk assessment. The capabilities of advanced data analytic sallow for various data inputs that may later affect the project in some way. Think of traffic data to precisely calculate the delivery of resources to the construction site or the analysis of weather data to avoid interruptions due to adverse weather-conditions.

2. Monitor ongoing processes of the construction site. Data input along the construction allows planners to constantly align the actual data with the data of the model and recognize deviations in real-time. Faster identification of mistakes and agility in adjusting of inefficiencies within the construction process are the result.

3. After finishing the production process there will be a complete database at hand. Including data about the entire production process and the execution of all steps of the production plan. This data can be used as a proof of work, a proof of sustainability, or to feed the BIM-systems for future projects.

Collaboration with governments and NGOs

Besides the selling-process a dataset linked to each individual fish. Customs checks could be largely simplified by providing all product-related data beforehand to have a definite proof of origin and compliance to import regulations (e.g. farming conditions or medicine given). Government organizations and NGOs are showing high interest in blockchain-based traceability to speed-up import processes.

Product-related data along the supply chain is recorded from growth to the consumer, that means that the salmon from this farm is fully traceable (learn more about traceability systems). A complete dataset can be presented to the consumer of the salmon, one of the big trends in today’s food and beverages industry.

BIM supports the construction process in three steps:
1. Plan the project assessing internal and external factors. A complete simulation of the building is being created in advance for more detailed visualization and a thorough risk assessment. The capabilities of advanced data analytic sallow for various data inputs that may later affect the project in some way. Think of traffic data to precisely calculate the delivery of resources to the construction site or the analysis of weather data to avoid interruptions due to adverse weather-conditions.

2. Monitor ongoing processes of the construction site. Data input along the construction allows planners to constantly align the actual data with the data of the model and recognize deviations in real-time. Faster identification of mistakes and agility in adjusting of inefficiencies within the construction process are the result.

3. After finishing the production process there will be a complete database at hand. Including data about the entire production process and the execution of all steps of the production plan. This data can be used as a proof of work, a proof of sustainability, or to feed the BIM-systems for future projects.