The Department of Agricultural and Food Sciences, University of Bologna, Italy has been looking into CANBUS-enabled activity-based costing for leveraging farm management. They have created a methodology that helps farmers to make operational decisions and create data that can be used for input into farm management information systems (FMIS).
As an example, a study showing a tractor active for 59% of the time was idling for 25% of the time. Fuel and labour costs represented from 63% to 71% of the total cost per hectare. The tractor was equipped with a CANBUS logger and Bluetooth beacons on several tractor implements to automatically recognise agricultural operations. The data was processed to classify jobs by position (field, farm, or road) and operating state (moving, fieldwork, or idling).
With such systems, farmers can determine the economic impact of farm activities and compare historical data with previous farm practices or competitors’ activities. This helps farmers make more intelligent decisions regarding crop, land and farm operations management.
The paper describes an IoT-based smart traceability and farm management system that calibrates irrigation and fertilisation based on crop typology, growth phase, soil and environment parameters and weather information.
The system uses a custom built Bluetooth LE sensor tag that’s fixed to containers agri-food products collected from the fields, being processed or stores. The sensor monitors gas, temperature and humidity that indicates whether the foods are spoiling over time or along the supply chain. The tag also supports traceability. A mobile application monitors the tracked information and condition of the agri-food products.
The sensor tag uses a HM-10 BLE module and CCS811 (gas) and BMP280 (temperature and humidity) sensors that were chosen to provide reliable markers of the freshness status of vegetables, meat and fish. The gas sensor measures Total Volatile Organic Compounds (TVOCs) and equivalent CO2 (eCO2) concentrations for air quality monitoring applications.
The developed system schedules irrigation and fertilisation according to the crops’ need reducing under or over watering thus minimising plants’ stress.
Smart farming allows farmers to control, in real time, the growth and harvest of cultivated crops. It allows agricultural companies to increase yields, nutritional quality and improve safety. It reduces production costs and the negative impacts on the environment for economic, environmental and social sustainability.
Researchers identified the behaviour and physiological state of milk cattle using beacons and combined this with data from weather forecast stations.
Changes of motor activity of cows were recorded on the 24hr characteristics and registered during the period of cattle heat. Motorola smartphones were used as base stations to collect and process the data.
The researchers succeeded in collecting and processing data from beacon devices that provided an alterative to traditional pedometer-based solutions.
The system automatically monitors vine stress to provide real-time surveillance and alerts. It identifies specific areas for irrigation, thereby saving water, energy and time.
The Bluetooth iBeacon protocol is used to relay temperature, humidity, UV levels and soil moisture levels. The authors modified the standard iBeacon protocol, using the existing iBeacon minor and major fields to encode the telemetry data.
It demonstrates the use of IoT to revolutionise farming. A system was implemented to provide for:
Optimum water and fertiliser use
Better quality and yield of crops
Reduction in production costs
Reduction in negative impacts on the health and environment
Sensors allow calibration of irrigation and fertilisation based on crop type, growth phase, soil and environmental conditions. The traceability allows monitoring of the movements of food products from the field, through storage to end consumers.
Bluetooth LE sensor tags are used for monitoring conditions during storage and transportation so as to assess freshness, integrity, as well as to provide for traceability.
The system enables enables management strategies that anticipate or delay crop collection, fine tuning the irrigation/fertilisation timing based on customers’ requests. This allows farmers to achieve economic benefits and reduce agri-food waste.
The authors have devised a hybrid system to reduce the cost compared to fitting every animal with a GPS LPWAN (Sigfox) tracker. While some GPS LPWAN (Sigfox) trackers are used, Bluetooth beacon collars are also used to lower the overall cost.
We believe an increasing number of tracking and sensing systems will use hybrid technologies.
Smart Farming, also sometimes known as the ‘Third Green Revolution’, is the use of IT to improve profitability, gain efficiency, reduce costs through making better, more optimal decisions and better management control.
Kristoffer Rist Skøien Senior R&D Engineer at Nordic Semiconductor, the making of the SoC in most beacons, has a recent blog post on Feeding the World with Connected Crops. He explains how farmers need to move beyond current precision agriculture (PA) and site specific crop management (SSCM) into more advanced realtime sensing of things such as weather conditions in a specific spot, soil humidity, soil acidity, growth progress and other productivity metrics.
IoT can improve the productivity of farming to improve yields, aid with cost management, waste reduction and automation to create a more efficient and productive business. In the future, this might even combine with autonomous vehicles for watering, fertilising and pesticide application.
There’s need to process significant amounts of data using game-changing business analytics at scale and at speed. Simple feedback mechanisms as well as complex deep learning algorithms can be combined with other, external data sources such as weather, market data or data from other farms. Techniques include benchmarking, analytics, predictive modelling and prognostics to provide models to manage crop failure risk.
A relatively recent paper, Big Data in Smart Farming – A review, covers the issues of extracting meaningful data from farm sensors. It explains the process from sensing and monitoring, through analysis and decision making to intervention with the implications on the efficiency of the entire supply chain. The paper covers the whole ecosystem that extends far from the farm itself:
Smart Farming is still in an early development stage. Current implementations are custom, proprietary solutions that can are experimental and expensive. Solutions need to be affordable, especially for developing countries. However, as with Industry, the early innovators will inevitably gain the early benefits while the laggards will get further left behind.
One way to reduce costs is using standard and open technologies. Bluetooth and more specifically, Bluetooth mesh, offers a low power, low cost, standard way of collecting sensor data. Open software platforms such as OpenATK and initiatives such as FIspace should make solutions more accessible.