Efficient Environmental Management and Monitoring System – SIGMA
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Efficient Environmental Management and Monitoring System – SIGMA
How can we optimize the environmental management of licenses, conditions, and contracts for Eletrobras assets through a robust and efficient solution that uses artificial intelligence?
The increasing stringency of environmental requirements and the complexity of regulatory processes have created significant challenges for companies in the energy sector, particularly those involved in power generation and transmission. The need to comply with environmental norms and regulations, coupled with the effective management of licenses and conditions, calls for a more agile and accurate approach.
Eletrobras’s large number of assets represents a challenge, but it also creates a strategic opportunity. Each asset has regional particularities (different biomes, federal, state, and municipal legislation, licensing methodologies, among others) that complicate the standardization of control processes. In this context, we seek solution proposals to optimize the management of environmental licenses and conditions for Eletrobras enterprises and assets, based on a clustering process that adopts specific premises and requirements, such as: Geographical location; Deadlines and renewals; Contracted companies involved; Conditions imposed by environmental agencies.
The solution must automate the extraction, classification, and analysis of information contained in environmental licenses (.pdf files) (based on legal requirements, licensing authority, scope of the environmental program, geographical location, among other factors), unifying contracts and processes of environmental programs and enabling integrated and efficient management. Furthermore, it should feature a dashboard with strategic indicators, a tool for generating detailed, analytical, and customizable reports for different management levels, allowing teams to effectively assess environmental performance and compliance. Environmental impact and cost reports should be easily accessible and understandable, supporting strategic decision-making.
Deadline: Proposal submission form will be available until 14/03/2025. Questions: For any questions or additional information, please send an email with the subject line identifying the title of this challenge to innovationgrid@eletrobras.com
Eletrobras’s large number of assets represents a challenge, but it also creates a strategic opportunity. Each asset has regional particularities (different biomes, federal, state, and municipal legislation, licensing methodologies, among others) that complicate the standardization of control processes. In this context, we seek solution proposals to optimize the management of environmental licenses and conditions for Eletrobras enterprises and assets, based on a clustering process that adopts specific premises and requirements, such as: Geographical location; Deadlines and renewals; Contracted companies involved; Conditions imposed by environmental agencies.
The solution must automate the extraction, classification, and analysis of information contained in environmental licenses (.pdf files) (based on legal requirements, licensing authority, scope of the environmental program, geographical location, among other factors), unifying contracts and processes of environmental programs and enabling integrated and efficient management. Furthermore, it should feature a dashboard with strategic indicators, a tool for generating detailed, analytical, and customizable reports for different management levels, allowing teams to effectively assess environmental performance and compliance. Environmental impact and cost reports should be easily accessible and understandable, supporting strategic decision-making.
Deadline: Proposal submission form will be available until 14/03/2025. Questions: For any questions or additional information, please send an email with the subject line identifying the title of this challenge to innovationgrid@eletrobras.com
Integrated Environmental Management | Licenses | Conditions | Generation Assets | Transmission Assets | Monitoring | Artificial Intelligence