Artificial Intelligence and IoT for tree health monitoring

Informations projet

TreeVoice

N° de convention de subvention: 824717

DOI

10.3030/824717

Projet clôturé

Date de signature de la CE 5 Septembre 2018

Date de début 1 Octobre 2018

Date de fin 31 Mars 2019

Financé au titre de

• INDUSTRIAL LEADERSHIP - Innovation In SMEs

Coût total

€ 71 429,00

Contribution de l’UE

€ 50 000,00

Coordonné par

TREEVOICE
Italy

Periodic Reporting for period 1 - TreeVoice (Artificial Intelligence and IoT for tree health monitoring)

Période du rapport: 2018-10-01 au 2019-03-31

Résumé du contexte et des objectifs généraux du projet

Treevoice is an ambitious and unique project exploiting IoT, Artificial Intelligence, M2M technologies and Structural Health Monitoring techniques to enable predictive maintenance of green areas and telecommunication infrastructures in urban and extra-urban scenarios. TREEVOICE ensures real time analysis of trees health and helps detecting harmful conditions leading to trees or wooden pole falls, which are a severe cause of damage to both citizens and the environment. The innovative sensor manufactured by Treevoice S.r.l. is able to sense and identify deviations in the normal vibration patterns, temperature and other environmental parameters in the wood, while the sophisticated machine learning algorithms in the cloud allow to predict and prevent falling events. The ambition of TREEVOICE is to help reducing of direct and indirect costs related to accidents caused by falls and maintenance of green areas and infrastructures in Smart Cities, boosting green growth.
The objective of this project is to validate the the innovative concept behind the TREEVOICE from a Business and Technical perspective through a campaign of field pilot installations performed on real customers. Thanks to this validation, Treevoice wants to consolidate the Business Model of the company, refine the technology of the sensor unit and empower the existing predictive and prescriptive maintenance algorithms.
Treevoice Srl aims now to achieve full maturity for the TREEVOICE system, and is willing to perform a validation project to achieve TRL 9 in 2022 from the current TRL7.

Travail effectué depuis le début du projet jusqu’à la fin de la période considérée dans le rapport et principaux résultats atteints jusqu’à présent

Thanks to the funding received through the Horizon2020 SME-Instrument Programme, Treevoice Srl managed to perform a complete Technical and Business Feasibility Study to validate the concept behind the product and experiment an MVP. During the 6 months of the project we achieved the following:
1. we installed 120 new units in a field testing campaign that allowed us to reach TRL7 stage for our services and algorithms.
2. we produced a final industrial design for the 3.0v of the sensor unit, and consolidated the Supply Chain for the pre-industrial prototype
3. we finalized the study of the business model behind the TREEVOICE product and services, quantified the pricing of the solution, license, and costs to maintain the operations
4. we produced a Business Plan, empowered competitor analysis, defined a go-to-market strategy with a 5-year Profit&Loss forecast and produced a SWOT analysis;
5. we have drafted a Phase 2 (PH2) project plan and budget;
We plan to accelerate our plan to reach the market and achieve TRL9 by 2022 presenting an application for a SME Instruament Phase 2 funding over a 2-years project with a total budget of 1.927.875€

Progrès au-delà de l’état des connaissances et impact potentiel prévu (y compris l’impact socio-économique et les conséquences sociétales plus larges du projet jusqu’à présent)

TREEVOICE‘s ambition is to revolutionize the way trees, green areas and infrastructures in Smart Cities environments are maintained and monitored, thanks to its unparalleled mixture of IoT and AI technologies.
The feasibility study conducted during the Phase 1 project showed how the system could:
- Provide a technological alternative to the current gold standard practice used in tree maintenance and protection, and ultimately reduce direct costs
- Be able to assess a fall prediction index for each monitored tree and produce meaningful alerts that were confirmed by on-site inspection, assessing the accuracy of the approach and algorithm
- Be able to assess the need for pruning in a preventive way, reducing the need for visual inspection and personnel costs
- Assess potential damage to urban infrastructures by applying the same algorithms and technologies to assets different from trees, demonstrating the versatility of the product

Closeup of installation performed in Tecnopolo Tiburtino, Rome

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