Periodic Reporting for period 3 - AFarCloud (Aggregate Farming in the Cloud)
Reporting period: 2020-09-01 to 2021-11-30
AFarCloud will provide a distributed platform for autonomous farming that will allow the integration and cooperation of agriculture Cyber Physical Systems in real-time in order to increase efficiency, productivity, animal health, food quality and reduce farm labour costs. This platform will be integrated with farm management software and will support monitoring and decision making solutions based on big data and real time data mining techniques. The AFarCloud project also aims to make farming robots accessible to more users by enabling farming vehicles to work in a cooperative mesh, thus opening up new applications and ensuring reusability, as heterogeneous standard vehicles can combine their capabilities in order to lift farmer revenue and reduce labour costs. The most important objectives achieved in AFarCloud project are listed below:
OBJ 1. To ease and aggregate solutions for the agriculture environment characterization
OBJ 2. To facilitate the creation of hierarchical mission plans involving elements working in an autonomous manner.
OBJ 3. A more efficient use of the available farming vehicles by means of a “sensing-on-the move” approach.
OBJ 4. Improvement of traditional business models and development of new ones.
OBJ 5. Demonstration of efficient and feasible solutions in real application scenarios.
OBJ 1. To ease and aggregate solutions for the agriculture environment characterization
OBJ 2. To facilitate the creation of hierarchical mission plans involving elements working in an autonomous manner.
OBJ 3. A more efficient use of the available farming vehicles by means of a “sensing-on-the move” approach.
OBJ 4. Improvement of traditional business models and development of new ones.
OBJ 5. Demonstration of efficient and feasible solutions in real application scenarios.
Within WP1 was developed according to the foreseen objectives, by coordinating and monitoring all project activities to ensure conformance with the project schedule during its whole lifetime, organizing and cordinating the project meetings, the administrative issues, the risk management, technical coordination of the project and quality control assurance.
WP2:
• Specification of the AFarCloud smart farming platform’s architecture for crops and livestock monitoring and for the management of missions with heterogeneous vehicles including drones, UGVs and tractors
• AFarCloud-as-a-Service secure communication infrastructure.
• Interoperable distributed cloud-based middleware solution for the management of data, devices and images, and for sending commands to actuators
• Mission management of cooperating autonomous & heterogeneous vehicles in real-time
• Prescription maps generation for ISOBUS tractors and monitoring of treatment logs
• End to end security mechanisms for the services.
• Blockchain infrastructure for smart farming use cases
• Secure in-vehicle Over-The-Air (OTA) software updates
• Secure firmware updates for sensors.
WP3:
• A methodology for transforming agricultural activities of different durations and complexities to mission abstraction
• Integrated approach for mission management.
• Continuous monitoring by using decision-support systems (DSS) of agricultural missions.
• System configuration for integration of heterogeneous hardware, and software.
• Allowing autonomy of heterogeneous robotic systems.
WP4:
• Pre-processing and data fusion on multi-spectral, thermal, and video images and for sensor data. and allows access to farm data in trusted or standard data formats (e.g. ISOBUS, NCDX)
• Developed large variety of algorithms for environmental monitoring
• Developed large variety of algorithms for crops and livestock management functionalities
• Provide environment independent services to the operator for monitoring and managing the farm
• Developed innovative cloud monitoring (availability, performance, location)
• Visualization of algorithms in the diffrente GUIs
WP5:
Crop:
• Beyond state-of the-art wireless sensors network for soil parameters with flexibility for implementation and communication.
• Soil models for water management and vehicle trafficability.
• AI training algorithms for vehicle work status & localization.
• Smart hub for in-vehicle implements for in-vehicle sensor data integration.
• Soil models for water management and vehicle trafficability.
• AI training algorithms for livestock wellbeing and for vehicle work status & localization
• Actuators final implementation for greenhouse.
• Energy harvesting using RFID reading from drone of ground sensor data.
• Environmental sensors (e.g. temp, humidity, air quality) installed in the field and integrated with AFarCloud platform.
• Camera on drones for crop/ grass growth and parameters monitoring (e.g. multispectral, thermal, NIR) and their specific image processing algorithms and platform (together with WP4).
Livestock
• Environmental sensors cowshed (e.g air temperature, humidity, CO2) installed and integrated to AFarCloud platform.
• Wearable collars with Edge AI + sensors.
• Cow rumen scanner combined with Time-of-flight technology and e-tag RFID reader.
• Ruminal sensor.
Actuators
• water actuator integration for greenhouse.
• Tractor implement (e.g. spreader rate).
• Crop irrigation.
Gateways & WSN
• LoRaWAN, BLE, NB IoT, Sigfox, 3G/4G implemented for crop and livestock.
• UWB, RTLS/ TDoA for indoor cow positioning.
• ISObus, CANbus and secure GW ‘Smart Hub’ tractor.
WP6:
• A methodology for developing autonomous systems.
• Development of tools for safety and security testing.
• Integration between operators, MMT (and mobile MMT), and UAVs and UGVs.
• Integration of legacy systems with the Semantic Middleware and MMT.
• Development of the HLAF (Framework for high-level awareness) including integration in MMT.
• Integration of Tractor Terminal (TTC’s HMI) and Gateways (in tractor and ISOBUS).
• Development of the soil analysis robot and systems analysis for HARA.
• Integration of Drones (AGVs and UAVs) in the AFarCloud platform and integration of new hardware (sensors).
• Development of the first prototype of the UAS manipulator.
• Implementation of services for positioning and mapping in autonomous legacy systems.
WP7:
• AFarCloud platform was integrated and deployed in all 11 scenarios and utilizied in their daily operations.
• 27 Functionalities were realized, where WP2-6 contributions were put to contribute to the real farmer needs with concrete solutions. All these were deployed and evaluated in real farm conditions by the demonstration farmers.
• Altogether 9 potential product ideas were identified and analyzed against SoA. Their development is expected to continue after the project
WP8:
• Distributed and analysed power users’ questionnaires with WP7
• Drafted and distributed networking guidelines for the entire consortium
• Written a comprehensive servitization analysis
• Created a possible FaaS roadmap and strategy
• Market & applicability analysis delivered
• New business models defined
• Updated exploitation plans
• Full list of AFC product and services prepared
• Joint collaboration performed as a result of networking meetings
• Dissemination & communication strategy updated
• Channelled communication and dissemination (based on stakeholder type)
• Dedicated AFC communication campaign performed
• Dissemination and communication activities performed as specified in D8.4
WP2:
• Specification of the AFarCloud smart farming platform’s architecture for crops and livestock monitoring and for the management of missions with heterogeneous vehicles including drones, UGVs and tractors
• AFarCloud-as-a-Service secure communication infrastructure.
• Interoperable distributed cloud-based middleware solution for the management of data, devices and images, and for sending commands to actuators
• Mission management of cooperating autonomous & heterogeneous vehicles in real-time
• Prescription maps generation for ISOBUS tractors and monitoring of treatment logs
• End to end security mechanisms for the services.
• Blockchain infrastructure for smart farming use cases
• Secure in-vehicle Over-The-Air (OTA) software updates
• Secure firmware updates for sensors.
WP3:
• A methodology for transforming agricultural activities of different durations and complexities to mission abstraction
• Integrated approach for mission management.
• Continuous monitoring by using decision-support systems (DSS) of agricultural missions.
• System configuration for integration of heterogeneous hardware, and software.
• Allowing autonomy of heterogeneous robotic systems.
WP4:
• Pre-processing and data fusion on multi-spectral, thermal, and video images and for sensor data. and allows access to farm data in trusted or standard data formats (e.g. ISOBUS, NCDX)
• Developed large variety of algorithms for environmental monitoring
• Developed large variety of algorithms for crops and livestock management functionalities
• Provide environment independent services to the operator for monitoring and managing the farm
• Developed innovative cloud monitoring (availability, performance, location)
• Visualization of algorithms in the diffrente GUIs
WP5:
Crop:
• Beyond state-of the-art wireless sensors network for soil parameters with flexibility for implementation and communication.
• Soil models for water management and vehicle trafficability.
• AI training algorithms for vehicle work status & localization.
• Smart hub for in-vehicle implements for in-vehicle sensor data integration.
• Soil models for water management and vehicle trafficability.
• AI training algorithms for livestock wellbeing and for vehicle work status & localization
• Actuators final implementation for greenhouse.
• Energy harvesting using RFID reading from drone of ground sensor data.
• Environmental sensors (e.g. temp, humidity, air quality) installed in the field and integrated with AFarCloud platform.
• Camera on drones for crop/ grass growth and parameters monitoring (e.g. multispectral, thermal, NIR) and their specific image processing algorithms and platform (together with WP4).
Livestock
• Environmental sensors cowshed (e.g air temperature, humidity, CO2) installed and integrated to AFarCloud platform.
• Wearable collars with Edge AI + sensors.
• Cow rumen scanner combined with Time-of-flight technology and e-tag RFID reader.
• Ruminal sensor.
Actuators
• water actuator integration for greenhouse.
• Tractor implement (e.g. spreader rate).
• Crop irrigation.
Gateways & WSN
• LoRaWAN, BLE, NB IoT, Sigfox, 3G/4G implemented for crop and livestock.
• UWB, RTLS/ TDoA for indoor cow positioning.
• ISObus, CANbus and secure GW ‘Smart Hub’ tractor.
WP6:
• A methodology for developing autonomous systems.
• Development of tools for safety and security testing.
• Integration between operators, MMT (and mobile MMT), and UAVs and UGVs.
• Integration of legacy systems with the Semantic Middleware and MMT.
• Development of the HLAF (Framework for high-level awareness) including integration in MMT.
• Integration of Tractor Terminal (TTC’s HMI) and Gateways (in tractor and ISOBUS).
• Development of the soil analysis robot and systems analysis for HARA.
• Integration of Drones (AGVs and UAVs) in the AFarCloud platform and integration of new hardware (sensors).
• Development of the first prototype of the UAS manipulator.
• Implementation of services for positioning and mapping in autonomous legacy systems.
WP7:
• AFarCloud platform was integrated and deployed in all 11 scenarios and utilizied in their daily operations.
• 27 Functionalities were realized, where WP2-6 contributions were put to contribute to the real farmer needs with concrete solutions. All these were deployed and evaluated in real farm conditions by the demonstration farmers.
• Altogether 9 potential product ideas were identified and analyzed against SoA. Their development is expected to continue after the project
WP8:
• Distributed and analysed power users’ questionnaires with WP7
• Drafted and distributed networking guidelines for the entire consortium
• Written a comprehensive servitization analysis
• Created a possible FaaS roadmap and strategy
• Market & applicability analysis delivered
• New business models defined
• Updated exploitation plans
• Full list of AFC product and services prepared
• Joint collaboration performed as a result of networking meetings
• Dissemination & communication strategy updated
• Channelled communication and dissemination (based on stakeholder type)
• Dedicated AFC communication campaign performed
• Dissemination and communication activities performed as specified in D8.4
The Section 2.1 of the DoA is still relevant after the end of the project.
Besides enabling future growth and job creation in the European blue economy, AFarCloud will also help protecting the environment by making it possible detection, accurate identification and proper quantification of factors affecting plant and animal health, also the automation and optimization of laborious tasks, offering the possibility of doing for example, a selective harvesting, targeted weed reduction and fertilization, automated livestock management and planning.
Besides enabling future growth and job creation in the European blue economy, AFarCloud will also help protecting the environment by making it possible detection, accurate identification and proper quantification of factors affecting plant and animal health, also the automation and optimization of laborious tasks, offering the possibility of doing for example, a selective harvesting, targeted weed reduction and fertilization, automated livestock management and planning.