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Abstract

Enel Green Power (EGP) is looking for new tools to improve the environmental sustainability and biodiversity preservation of its renewable installations, as photovoltaic plants and/or wind farms. In particular, EGP is looking for solutions to be applied during the construction phase of renewable power plants to detect selected tree or other vegetation species, that may be rare, in danger of extinction, or of particular importance for the local biodiversity equilibrium of the considered area, or that are protected by regulation. Improperly identified plant species during the preliminary phase of a project could delay the renewable plant construction.

This Theoretical Challenge requires only a written proposal.

 

OVERVIEW

Enel Green Power (EGP), a global leader in the development and management of energy production from renewable sources (wind, solar, hydroelectric, and geothermal), is aware of the value of the ecosystems and of biodiversity and is committed to the responsible management of natural resources along the construction phase of new plants. EGP, pursuing the target of a 100% renewable generation, is opening, and managing new construction site in the Countries where it is present, always looking for new tools and techniques to enable strategies aimed at improving the environmental sustainability and guaranteeing biodiversity preservation of its renewable installations. Protected tree species, not properly detected and identified during the preliminary phase of construction projects, could lead to delays to project timelines, costly redesign works or even bring the entire construction site activities to a halt.

In particular, EGP is looking for artificial intelligence (AI) solutions to be applied during the construction phase of renewable power plants to detect selected tree or other vegetation species, that may be rare, in danger of extinction, or of particular importance for the local biodiversity equilibrium of the considered area, or that are protected by regulation.

This Challenge provides contribution to the following SDGs:

For questions about the challenge and your proposal you can contact EnelOpenInnovabilityChallenges@wazoku.com

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Description

BACKGROUND

During construction projects, the presence of protected tree species, not properly detected and identified during the preliminary project phase, could lead to delays to project timelines, costly redesign works or even bring the entire construction site activities to a halt. These situations if properly managed in advance by adopting effective and efficient techniques and methods to detect protected tree or other vegetation species, that may be rare, in danger of extinction, or of particular importance for the biodiversity equilibrium of the considered area, or that are protected by regulation, can be leveraged to transform a potential issue into opportunities to add value to the project.

In compliance with local legislation, Enel Green Power carries out manual investigations to evaluate and manage this task, combining traditional and innovative technology systems, in order to detect protected tree species in an early stage of the construction project, and to identify areas where further detailed investigations are needed. Protected tree species search and survey, traditionally carried out by expert personnel, represent a considerable effort in terms of time, and they are often not compatible with project timelines, in particular when they are carried out over large areas of hundreds or thousands of hectares.

Below are some examples of rare species alongside vegetation that is of no concern.

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THE CHALLENGE

Enel Green Power (EGP) is looking for new tools to improve the environmental sustainability and biodiversity preservation of its renewable installations, as photovoltaic plants and/or wind farms. In particular, EGP is looking for solutions to be applied during the construction phase of renewable power plants to detect selected tree or other vegetation species, that may be rare, in danger of extinction, or of particular importance for the local biodiversity equilibrium of the considered area, or that are protected by regulation.

Proposals should include artificial intelligence (AI) technologies that allow the detection of selected tree species using high resolution and, if necessary, multispectral satellite images. The solution will have to identify only the desired species, without the need to recognize the surrounding species. The solution must have an excellent degree of probability of the recognition of the species, in order to mitigate as much as possible the risk during the construction phase of the plant. The solution must use, as input, satellite images in different environmental scenarios such as plains, hills or deserts, taken in different areas of the world such as Latin America, South Africa, Europe, India, etc. This list is not exhaustive, and the images could address additional Countries or scenarios. For areas partially or completely uncovered, the proposed solution should be trained within 3 to 6 months. The tree species that the solution will have to recognize belong to rare species, in danger of extinction, or of particular importance for the considered area’s biodiversity preservation. The solution is intended for use as an initial screening tool prior to confirmation of the results through manual investigation by field workers.

 

SOLUTION REQUIREMENTS

Submissions should address the following Solution Requirements:

The proposed solutions must:

  • be characterized by very high resolution (VHR) images (< 2 meter/pixel);
  • be applicable at least in Latin America, South Africa, Europe and India;
  • recognize rare species, species in danger of extinction, or of particular importance for the biodiversity preservation of the considered area – minimum of one species, maximum of ten species;
  • recognize the desired vegetation, the area where the vegetation species is present and/or the number of trees with a good level of confidence (90%).

Moreover, the solution should:

  • be based on multispectral satellite images;
  • be trained for uncovered areas within 3 to 6 months;
  • provide information about the tree health;
  • indicate, in certain contexts, the proximity of the tree to buildings, streets or wells.

 

PROJECT DELIVERABLES

The submitted proposal should include the following:

  • Detailed description of the proposed method and/or technique, including (but not limited to):
    • advantages and weaknesses of the proposed solution;
    • information about the accuracy in terms of type of species, number and location of selected tree species detectable and time required for the execution of surveys;
    • evidence or calculated probability of detection, if applicable;
    • information about its applicability (i.e. type of areas/Countries, weather conditions);
    • estimate of the computing power needed to implement the proposed approach.
  • Data, case studies, patent and journal references or any additional material that supports the proposed solution.

The proposal should not include any personal identifying information (name, username, company, address, phone, email, personal website, resume, etc.) or any information the Solvers may consider as their Intellectual Property they do not want to share.

Challenge rules

All proposers are invited to read carefully the Challenge and the Regulation of this Challenge, attached below in the Attachments section, before submitting a solution.

By submitting a solution they automatically accept the attached Regulations other than the Terms of Use of this platform.

 

ELIGIBILITY

The employees of Enel Green Power and of the other Companies of the Enel Group who are involved in the organization and management of the Competition or admitted to the Open Innovability Portal back office, as well as their spouses or partners and their relatives up to the fourth degree, are not eligible for participation in this Challenge.

Also, employees of the companies of the Enel Group who have worked in the technical sector of artificial intelligence and that work, in the moment of the Challenge, on visualization algorithms, or their spouses, partners or any of their relatives up to the fourth grade determined according to Italian law are not eligible for the participation in this Challenge.

Without prejudice to the article 5.5 of the Terms of Use, the obligation to grant the IP rights set in this article does not apply if the winning solution is proposed by an employee of an Enel company, unless the employee is the owner of the solution according to the relevant national law.

Explain your proposal clearly in English, attach documents (max 5 files, 25MB total size) if needed.

The proposals will be admitted until February 28, 2022 and the evaluation will start after this date.

All proposers are invited to read carefully the challenge and the regulation of this contest before to submit a solution. By submitting a solution they automatically accept the Regulations other than the Terms of Use of this platform.

This is a Theoretical Challenge, which requires only a written proposal to be submitted. The Challenge award will be contingent upon theoretical evaluation of the submission by the Seeker.

To receive an award, the Solvers will not have to transfer the exclusive IP rights to the Seeker. Instead, Solver will grant to the Seeker a non-exclusive license to practice their solutions.

 

DEADLINE

Submissions to this Challenge must be received by 11:59 PM (Central European Time) on February 28, 2022.

Late submissions will not be considered.

Specific regulation in the CSA attached at the bottom of this page.

Regulation

Enel Regulation - Theoretical Challenge CSA - AI for Protected Vegetation Recognition

PDF (0.42MB) Download

What happens next?

After the Challenge deadline, the Seeker will complete the review process and make a decision with regards to the Winning Solution(s). All Solvers that submit a proposal will be notified on the status of their submissions.

Enel will evaluate the proposal using the following criteria:

  • Overall scientific and technical feasibility of the proposed solution;
  • Economic potential of concept (e.g. Total Cost of Ownership);
  • Business potential for Enel;
  • Novelty and not obviousness;
  • Potential for proprietary position (i.e., is the technology novel or protectable);
  • User’s capabilities and related experience;
  • Realism of the proposed solution;
  • Maturity level of the proposal.

If the reward includes the opportunity to collaborate with Enel, once one or more suitable solutions have been identified, Enel will reserve the opportunity to start a collaboration, by way of example, on all or part of the following activities:

  • Test execution;
  • Supply of prototypes (if the solution includes equipment);
  • Installation and site tests;
  • Follow up and monitoring of the proposed idea behavior.

Upon completion of the evaluation, you will receive feedback.

In case of success, an Enel contact person will get in touch with you to discuss the next steps.

The final award for this Challenge is contingent upon satisfactory completion of the verification process, including acceptance of the Challenge-Specific Agreement (CSA) that is the regulation for this Challenge.
The verification process includes obtaining the following from the Solver: signed affidavit (based on the CSA), employee waiver (if applicable), proof of identify, and Counterparty Analysis Questionnaire (CAQ).

 

ABOUT INNOCENTIVE

InnoCentive collaborates with Enel to manage this Challenge.
InnoCentive is the global innovation marketplace where creative minds solve some of the world's most important problems for cash awards up to $1 million. Commercial, governmental and humanitarian organizations engage with InnoCentive to solve problems that can impact humankind in areas ranging from the environment to medical advancements.

Attachments

Figure 1. Example of trees classification in a temperated forest

JPG (0.26MB) Download

About the seeker Enel - Enel Green Power

PDF (0.09MB) Download

Enel Regulation - Theoretical Challenge CSA - AI for Protected Vegetation Recognition

PDF (0.42MB) Download

Figure 2. Trees classification using satellite images and AI

JPG (0.22MB) Download

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