Task 3.1 intelligent tree marking (by cnr)
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Transcript of Task 3.1 intelligent tree marking (by cnr)
Task 3.1 – Intelligent tree marking
Kick-off Meeting 8-9/jan/2014
Tree marking in selective cuts
Key operation in forestry affecting cost of harvest operations, environment, ecology, etc.
Forest inventory integration
Task 3.1 – Intelligent tree marking
Kick-off Meeting 8-9/jan/2014
An optimal organization of work implies tree marking after the definition of the hauling direction (and the extraction system).
The forester should have access to full information about the forest and the harvesting system
-> one of the goal of SLOPE
Task 3.1 – Intelligent tree marking
Kick-off Meeting 8-9/jan/2014
Marks must be easy to recognize
Different systems can be used (debarking, colours)
The new marking will couple with traditional system
Task 3.1 – Intelligent tree marking
Kick-off Meeting 8-9/jan/2014
Participants: - CNR- MHG- BOKU- GREIFEMBERG- TREMETRICS- ITENE
Interactions:- WP3. direct interactions tasks 3.2, 3.3, 3.4;- WP2. task 2.4 (3D modeling for harvesting planning) Virtual Forest Model which ideally will be implemented in the marking phase (M8-15);- WP5. task 5.1 (Database to support novel inventory data content) where a RFID code to single entry indexing is envisaged (M8-17).
Start M6, end M17 (May 2015)
Deliverables (both due in M17):D3.01 Portable RFID tag reader/programmerD3.02 RFID tag test
Task 3.1 – Intelligent tree marking
Kick-off Meeting 8-9/jan/2014
CNR, BOKU, GRE
high-precision GPS and rugged PC
• position of the planned cable-crane skyline• the plot’s boundaries • single trees already identified as candidates (WP2) • visualize the related information• potentially input new info in the database (species, diameter, defects, wildlife, etc.)
Deadline M17, by M12 a interim delivery report should be prepared
Task 3.1 – Intelligent tree marking
Kick-off Meeting 8-9/jan/2014
ITENE, MHG, TRE
RFID UHF tags, a programming/reading tool (possibly the former rugged PC) and an inserting device
• effectively marking trees• easy to place and to read• robust and long-lasting• definition of the most appropriate position in the standing tree• programmable blank tag or index association to database for unique identity tags • association of traditional marking (color, debarking) with IT marking
Deadline M17, by M12 a interim delivery report should be prepared
Task 3.1 – Intelligent tree marking
Kick-off Meeting 8-9/jan/2014
Many possible options
• nail shaped RFID tags• mixed UHF and color/barcode tags• others
Important is the interaction with the following steps of felling, hauling and processing (tasks 3.2-3.4)
Task 3.1 – Intelligent tree marking
Kick-off Meeting 8-9/jan/2014
Different solutions for different work stages?
• edge shaped RFID tag• butt position (only on felled trees or logs)• potentially bridging in task 3.4
Task 3.1 – Intelligent tree marking
Kick-off Meeting 8-9/jan/2014
Ergonomics in mountain forest is crucial
Devices must be light, compact, tough, waterproof and reliable
Task 3.1 – Intelligent tree marking
Kick-off Meeting 8-9/jan/2014
ChallengesThe chosen system will influence all the traceability performance
A cumbersome or heavy system would not be accepted by operators
The survival rate and reading success rate must be high and secured over a reasonable span of time
Interaction among tags and machines as well as tag readers and ERP is crucial
Task 3.1 – Intelligent tree marking
Kick-off Meeting 8-9/jan/2014
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
1 Definition of requirements and system analysis
1.1 Users and System requirements
1.2 Hardware and equipment definition
1.3 Human Machine Interface (HMI) definition
1.4 Mountainous Forest inventory data model definition
1.5 System architecture
2 Forest information collection
2.1 Remote sensing and multispectral analysis
2.2 UAV data acquisition and processing
2.3 On-field digital survey systems
2.4 3D Modelling for harvesting planning
2.5 Road and Logistic planning
3 Complex machine system
3.1 intelligent tree marking X X
3.2 intelligent tree felling/haulin
3.3 Intelligent Cable crane (improvement)
3.4 intelligent processor head
3.5 intelligent transport truck
3.6 data management back-up
4 Multi-Senror Model-based quality control of mountain
4.1 Data mining and model integration of stand quality indicators from
4.2 Evaluation of near infrared spectroscopy as a tool
4.3 Evaluation of hyperspectral imaging (HI) for the determination of
4.4 Data mining and model integration of log/biomass quality
4.5 Evaluation of cutting process (CP) for the determination of
4.6 Implementation of the log/biomass grading system
5 Forest information system development
5.1 Database to support novel inventory data content
5.2 Platform for near real time control of operations
5.3 Online purchasing/invoicing of industrial timber and biomass
5.4 Long term optimization; strategic planning
5.5 Mid-long term optimization; strategic and tactical planning
6 System Integration
6.1 Definition of the integration steps
6.2 First Integration – Forest inventory & harvesting systems
6.3 Second integration – Forest management
6.4 Third integration -System validation
7 Piloting the SLOPE demonstrator
7.1 Definition of evaluation methodology
7.2 Preparation and deployment of demonstrators
7.3 Trials Recommendations and validation cycle
7.4 Training