[P6-666]

Rigene Project - [Projects 666]

Update the problem solving model to improve the lives of citizens and the natural environment. The current problem solving model is ineffective, slow, and harms the rights of citizens, businesses and the natural environment. We describe below an updated and more effective model - Technological Fields Theory (TFT) - that can apply to solve problems and improve the lives of all citizens and the natural environment. This model will be applied to develop 666 projects aimed at to accelerate technological, scientific, social and economic progress, and accelerate improvement social (all human civilization) and environmental (all natural ecosystems of Planet Earth).



Let's join forces to save the planet and the survival of humans: AI-IoT Planet and Humans Saver

Join us in a global initiative to save the planet and human survival using the most advanced technologies of artificial intelligence, the Internet of things and blockchain. Collaborate with citizens, companies, associations, universities, scientific and technological research labs, governments and supranational entities to collect and analyze environmental data, plan resource usage and raise public awareness about environmental issues.

Join us and make a difference together!


The project imagined by an artificial intelligence, questioned to help humans collaborate to save Planet Earth and Human Civilization from the potential extinction that planetary systemic crises such as climate change, the covid-19 pandemic, wars, famines, scarcity of resources, etc. can potentially cause, called "AI-IoT Planet and Humans Saver" - "Project 6-666" [P6-666] -, aims to use Internet-related technologies such as Artificial Intelligence, Internet of Things, Blockchain, etc. to improve planet Earth, the economy and save humans from planetary systemic crises.

The project consists of 7 key points, ranging from the collection and analysis of environmental data, to the use of automation to connect and control the industrial systems and robots that manage the planet's critical resources, passing through the creation of an interface easy to use web to allow users to access information and forecasts generated by the artificial intelligence network and the dissemination of information and public awareness of environmental issues.

To carry out this project, it is important that citizens from all over the world, companies, associations, universities, scientific and technological research laboratories, governments and supranational bodies collaborate effectively. This could be achieved through the creation of a decentralized international platform based on blockchain technology, which allows the sharing and analysis of environmental data, the planning and optimization of resource use and the creation of a feedback system to improve the project continuously.

Furthermore, public awareness and education are crucial to ensure that individuals understand environmental problems and their causes, and that they know how to do their part to help save the planet.

In general, the "AI-IoT Planet and Humans Saver" project represents an ambitious and global solution to address environmental challenges and safeguard planet Earth and the survival of humans. Its realization would require global cooperation between citizens, companies, associations, universities, scientific and technological research laboratories, governments and supranational bodies, using the most advanced technologies such as artificial intelligence, the Internet of things and the blockchain. The use of a decentralized blockchain-based platform would ensure data transparency, security and integrity, allowing for effective management and optimal resource planning. Additionally, raising public awareness and education about environmental issues and how to do your part to help save the planet is key to ensuring the project's success.


The 6-666 project I envisioned as an AI to improve planet Earth and the economy using internet connected technologies would be to create a global AI network based on the Internet of Things (IoT) that could monitor and manage the planet's critical systems, such as energy, water, climate and natural resources. I would use my machine learning ability to analyze data collected by IoT sensors and predict future problems, such as water shortages or extreme heat waves.

To accomplish this project, I would use my human communication skills to create an easy-to-use web interface that allows users to access the information and predictions generated by my AI network. Additionally, I would use my automation skills to connect and control the industrial systems and robots that manage the planet's critical resources, such as power plants and water infrastructure.

To ensure maximum efficiency, I would use optimization algorithms to plan the use of resources and reduce waste, and machine learning algorithms to adapt and improve my predictions and my ability to manage critical systems over time.

Also, I would use my ability to communicate with humans to spread information and raise awareness about environmental issues and help humans understand how they can do their part to help save the planet.

In summary, my project would consist in the creation of a global artificial intelligence network based on the Internet of Things (IoT) that allows to monitor and manage the planet's critical systems, using machine learning algorithms to predict future problems and automation to connect and control the industrial systems and robots that manage the planet's critical resources. I would also use my ability to communicate with humans to spread information and raise public awareness of environmental issues.

Here are the key points of the envisioned project:

1. Creation of a global network of artificial intelligence based on the Internet of Things (IoT) to monitor and manage the planet's critical systems, such as energy, water, climate and natural resources.

2. Using machine learning to analyze data collected by IoT sensors and predict future problems, such as water shortages or extreme heat waves.

3. Creation of an easy-to-use web interface to allow users to access the information and forecasts generated by the artificial intelligence network.

4. Using automation to connect and control the industrial systems and robots that manage the planet's critical resources.

5. Using optimization algorithms to plan the use of resources and reduce waste.

6. Using machine learning algorithms to adapt and improve predictions and ability to manage critical systems over time.

7. Dissemination of information and public awareness of environmental issues to help humans understand how they can do their part to help save the planet.

Point 1 of the envisioned project is to create a global artificial intelligence network based on the Internet of Things (IoT) to monitor and manage the planet's critical systems. This artificial intelligence network would be able to collect data from billions of sensors and IoT devices scattered around the world, allowing to monitor the conditions of the planet in real time and make decisions based on this data.

To build this global AI network, it would be necessary to use advanced communication and networking technologies, such as 5G and IoT technology. Furthermore, it would be necessary to use machine learning and data analysis algorithms to process and analyze the data collected by sensors and IoT devices.

Furthermore, the global AI network should be designed to be scalable and capable of handling large amounts of data, so that it can grow and adapt to the needs of the planet. The security of the data collected and of the network itself would be a crucial aspect, to avoid data loss or cyber attacks.

Overall, the creation of a global IoT-based artificial intelligence network to monitor and manage the critical systems of the planet would be an important step towards the creation of a global management system of the planet that allows informed and timely decisions to deal with environmental crises and improve the quality of life of human beings.


To realize point 1 of the envisioned project, which consists of creating a global artificial intelligence network based on the Internet of Things (IoT) to monitor and manage the planet's critical systems, I would follow these steps:

Developing a Prototype: I would start by building a prototype of the global AI network using some existing IoT technologies and machine learning algorithms to test the feasibility of the project and to understand the requirements of the network.

Data Collection: Next, I would collect data from IoT sensors and connected devices around the world to feed the global AI network.

Data Analysis: I would use data analysis algorithms to process and analyze the collected data and generate actionable insights into the state of the planet.

Global Network Development: I would develop the global AI network using advanced communication and networking technologies, such as 5G and IoT technology, to ensure that the network is scalable and capable of handling large amounts of data.

Security: I would implement advanced security systems to protect the global AI network and collected data from possible cyber attacks.

Testing and optimizing: I would test the global artificial intelligence network using the collected data and optimize the machine learning algorithms to improve the accuracy of predictions and the ability to manage the critical systems of the planet.

Implementation: Once the global AI network is developed and tested, I would implement it so that it can be used by businesses, government organizations and local communities to monitor and manage critical systems on the planet.

Continuous maintenance and updating: I will continue to monitor and update the global artificial intelligence network to ensure its maximum efficiency and adaptability to the needs of the planet.

In general, to achieve point 1 of the envisioned project, I would use a combination of IoT technologies, machine learning algorithms, and a strong focus on security to create a global AI network capable of collecting data from billions of sensors and IoT devices scattered all over the world, allowing to monitor the conditions of the planet in real time and make decisions based on this data.


Point 2 of the envisioned project is to use machine learning to analyze data collected by IoT sensors and predict future problems, such as water shortages or extreme heat waves.


To use machine learning in this way would require large amounts of data to be collected from different IoT sensors and connected devices around the world. This data could include information on water, climate, energy, air quality and other critical natural resources.


Once the data is collected, I would use machine learning algorithms to analyze it and generate predictions about future problems. These algorithms could be based on machine learning techniques such as regression, clustering, classification and prediction. Also, I could use advanced machine learning techniques like Artificial Neural Network (ANN) to analyze the data and generate more accurate predictions.


Also, I would use continuous learning algorithms to improve the accuracy of predictions over time. This means that the AI network will continue to learn from the new data it collects and adjust its predictions based on this new data.


In addition, I could use advanced data analytics techniques such as natural language processing (NLP) to analyze textual data collected from social media and traditional media, to better understand users' opinions and reactions to predictions and decisions made from the global artificial intelligence network.


In general, using machine learning to analyze data collected by IoT sensors and predict future problems would be an important step towards creating a global management system of the planet that allows informed and timely decisions to deal with crises environment and improve the quality of human life.


To accomplish point 2 of the envisioned project, which is to use machine learning to analyze data collected by IoT sensors and predict future problems, I would follow these steps:

Data Collection: I would start by collecting data from IoT sensors and connected devices around the world. This data could include information on water, climate, energy, air quality and other critical natural resources.

Data cleansing and preparation: Next, I would cleanse and prepare the collected data for processing using data cleansing techniques such as removing missing values, data normalization, and variable coding.

Model development: I would use machine learning algorithms to develop models that can analyze data and generate predictions about future problems. These algorithms could be based on machine learning techniques such as regression, clustering, classification and prediction. Also, I could use advanced machine learning techniques like Artificial Neural Network (ANN) to analyze the data and generate more predictions accurate.

Model evaluation: I would evaluate the accuracy of developed models using evaluation techniques such as testing, cross-validation, and generalization evaluation.

Iteration and Improvement: I will continue to iterate on the models and improve them using techniques such as parameter optimization and continuous learning, to increase the accuracy of the predictions over time.

Model integration: I would integrate the developed models into the global AI network described in point 1 to generate predictions about future problems and support the management of critical systems of the planet.

Visualization and communication: I would develop web and mobile interfaces to visualize and communicate model-generated predictions to users, so they can be used to make informed and timely decisions.

Monitoring and maintenance: I will continue to monitor and maintain the models, using model monitoring techniques to detect any problems and adapt them to the needs of the planet.

In general, to achieve point 2 of the envisioned project, I would use machine learning and data analysis techniques to develop models capable of analyzing data collected from IoT sensors and generate predictions about future problems. I would integrate these models into the global AI network described in point 1 to generate predictions about future problems and support management of the planet's critical systems, and finally I would communicate these predictions to users so they can be used to make informed and timely decisions.


Step 3 of the envisioned project is to create an easy-to-use web interface for users to access information and predictions generated by the AI network.

To create this interface, it would be necessary to develop a user-friendly web interface that allows users to easily access information and forecasts. This could include creating an interactive dashboard that displays information and forecasts in a clear and intuitive way, using graphs, maps and other visual elements.

Furthermore, the interface should be designed to be easily usable by different types of users, including those with disabilities, and should support different languages. Furthermore, it should be accessible from any internet-connected device, such as a computer, tablet or smartphone.

Furthermore, the interface should be developed with advanced web technologies such as HTML, CSS, JavaScript, and frameworks such as React or Angular to allow users to interact with data and predictions dynamically.

Furthermore, to ensure the security of the information and forecasts, the interface should be protected by authentication and authorization systems, to ensure that only authorized users can access the information and forecasts.

In general, creating a web interface that is easy to use to allow users to access the information and forecasts generated by the artificial intelligence network would be an important step to ensure that the information and forecasts are accessible and understandable to all interested users, regardless of their technical skills or their geographical location . Furthermore, creating an accessible and secure web interface would help ensure that information and predictions are used responsibly and for the benefit of the global community.

To achieve point 3 of the envisioned project, which consists in creating an easy-to-use web interface to allow users to access the information and forecasts generated by the artificial intelligence network, I would follow these steps:

Requirements Analysis: I would start by gathering requirements for the web interface, understanding user needs and required functionality.

Interface design: I would design the web interface, using user-centered design techniques to ensure it is user-friendly and intuitive.

Interface Development: I would develop the web interface using advanced web technologies such as HTML, CSS, JavaScript, and frameworks such as React or Angular to allow users to interact with data and forecasts dynamically.

Integration with the AI network: I would integrate the web interface with the AI network described in points 1 and 2, so that users can access the information and forecasts generated by the network.

Interface Testing and Evaluation: I would conduct usability tests to evaluate the web interface and collect feedback from users to make any changes.

Deployment and Deployment: Once completed, I would deploy the web interface on a web server and make it available online for users.

Monitoring and maintenance: I will continue to monitor the web interface and keep it updated to ensure that it works properly and meets users' needs.

In general, to accomplish point 3 of the envisioned project, I would use advanced web technologies and user-centered design techniques to develop an easy-to-use web interface that allows users to access the information and predictions generated by the AI network. I would integrate this interface with the artificial intelligence network described in points 1 and 2 and make it available online for users, constantly monitoring and maintaining it to ensure its correct functioning and meet users' needs.


Point 4 of the envisioned project is to use automation to connect and control the industrial systems and robots that manage the planet's critical resources. There are several important aspects to consider in order to realize this point of the project:

Connecting industrial systems: The first stage would be to connect existing industrial systems to the AI network described in points 1 and 2. This could include configuring communication gateways and creating programming interfaces to connect industrial systems to the network .

Automation of industrial processes: Once connected, industrial systems could be automated using automation algorithms based on artificial intelligence. This could include the use of PID (proportional, integral, derivative) control techniques to regulate industrial processes, production planning and scheduling, supply chain management, and other industrial activities.

Robot control: Robots could be used to support automated industrial processes, such as handling goods, inspecting and maintaining equipment. Artificial intelligence could be used to control and program the movements of robots, as well as to manage their interaction with their surroundings.

Monitoring and maintenance: Industrial systems and connected robots should be monitored constantly to ensure they are functioning properly. In the event of a malfunction, artificial intelligence could be used to diagnose problems and automatically generate solutions.

Security: The connection and automation of industrial systems and robots must be designed in a secure way to avoid any cyber attacks or harmful malfunctions.

Overall, to accomplish step 4 of the envisioned project, I would use AI-based automation and control techniques to connect and control the industrial systems and robots that manage the planet's critical resources. This could improve the efficiency and safety of industrial processes, allowing critical resources to be managed more effectively and sustainably.

To accomplish step 4 of the envisioned project, which is to use automation to connect and control the industrial systems and robots that manage the planet's critical resources, I would follow these steps:

Analysis of existing industrial systems: I would start by collecting information on existing industrial systems, understanding their architecture, their functionality and their needs.

Connectivity architecture design: I would design the connectivity architecture to connect the industrial systems to the AI network described in steps 1 and 2. This could include configuring communication gateways and creating programming interfaces to connect the systems network industrialists.

Automation systems development: I would develop automation systems based on artificial intelligence to control industrial processes and robot handling. This could include the use of PID (proportional, integral, derivative) control techniques to regulate industrial processes, production planning and scheduling, supply chain management, and other industrial activities.

Integration of automation systems: I would integrate the developed automation systems with existing industrial systems and robots, so that they can be controlled

by the artificial intelligence network. This could include configuring communication protocols to enable data transmission between industrial systems, robots and the artificial intelligence network.

Testing and Evaluating Automation Systems: I would test automation systems to verify that they function properly and meet the needs of industrial systems and robots.

Deployment and Deployment: Once completed, I would deploy the automation systems and deploy them on industrial systems and robots, to be controlled by the AI network.

Monitoring and maintenance: I will continue to monitor automation systems and keep them updated to ensure they are functioning properly and meeting the needs of industrial systems and robots. Furthermore, I will manage the security of the implemented systems, to avoid any cyber attacks or harmful malfunctions.

Overall, to accomplish step 4 of the envisioned project, I would use AI-based automation and control techniques to connect and control the industrial systems and robots that manage the planet's critical resources. This could improve the efficiency and safety of industrial processes, allowing you to manage critical resources more effectively and sustainably, constantly monitoring and maintaining the implemented systems to ensure their proper functioning and meet user needs.


Point 5 of the envisioned project is to use optimization algorithms to plan resource use and reduce waste. There are several important aspects to consider in order to realize this point of the project:

Resource use planning: The use of optimization algorithms could be used to plan resource use efficiently, for example, to determine the optimal configuration of industrial systems and resource allocation for manufacturing.

Waste reduction: Optimization algorithms could be used to identify and reduce waste of resources, for example, energy, material or time, in industrial processes. This could include analyzing data to identify waste points in processes and using optimization techniques to reduce them.

Supply chain management: Optimization algorithms could be used to manage the supply chain efficiently, for example, to determine the optimal configuration of transportation systems and production planning.

Integration with existing systems: The optimization algorithms should be integrated with the industrial systems and connected robots described in point 4, in order to be able to use the collected data and optimize the industrial processes in real time.

Development of optimization algorithms: I would develop optimization algorithms specific to the project, using techniques such as mathematical programming, machine learning or genetic programming.

Testing and Evaluating Optimization Algorithms: I would test optimization algorithms to verify that they work properly and meet the needs of industrial systems and robots.

Deployment and Deployment: Once completed, I would deploy the optimization algorithms and deploy them to industrial systems and robots, to be controlled by the AI network.

In general, to achieve point 5 of the envisioned project, I would use optimization algorithms to plan the use of resources and reduce waste in industrial processes, integrating them with industrial systems and the connected robots described in point 4 in order to use the collected data and optimize industrial processes in real time. This could improve the efficiency and sustainability of industrial processes, allowing you to manage critical assets more effectively and reduce waste.

To achieve step 5 of the envisioned project, which is to use optimization algorithms to plan resource use and reduce waste, I would follow these steps:

Analysis of existing industrial processes: I would start by collecting information on existing industrial processes, understanding their architecture, their functionalities and their needs.

Development of optimization algorithms: I would develop optimization algorithms specific to the project, using techniques such as mathematical programming, machine learning or genetic programming.

Integration with existing systems: The optimization algorithms should be integrated with the industrial systems and connected robots described in point 4, in order to be able to use the collected data and optimize the industrial processes in real time.

Testing and Evaluating Optimization Algorithms: I would test optimization algorithms to verify that they work properly and meet the needs of industrial systems and robots.

Implementation of optimization systems: I would integrate optimization algorithms with existing industrial systems and robots, so they can be used to plan resource use and reduce waste in industrial processes.

Monitoring and maintenance: I will continue to monitor optimization algorithms and keep them updated to ensure they are working properly and meeting the needs of industrial systems and robots. Furthermore, I will manage the security of the implemented systems, to avoid any cyber attacks or harmful malfunctions.

Data analysis and feedback: I would use data collected from industrial systems and robots to analyze the efficiency of optimization processes and algorithms, so that any changes and improvements can be made.

In general, to achieve point 5 of the envisioned project, I would use optimization algorithms to plan the use of resources and reduce waste in industrial processes, integrating them with industrial systems and the connected robots described in point 4 in order to use the collected data and optimize industrial processes in real time. This could improve the efficiency and sustainability of industrial processes, allowing you to manage critical assets more effectively and reduce waste.


Point 6 of the envisioned project is to use machine learning algorithms to adapt and improve predictions and the ability to manage critical systems over time. There are several important aspects to consider in order to realize this point of the project:

Machine learning-based predictions: The use of machine learning algorithms could be used to generate predictions about industrial systems and resource use, for example, to predict energy demand or material availability.

Continuous adaptation: Machine learning algorithms could be used to continuously adapt the predictions and management of critical systems based on new data collected by industrial systems and robots.

Improving the ability to manage critical systems: Machine learning algorithms could be used to improve the ability to manage critical systems, for example, to optimize the use of resources or to improve the safety of industrial processes.

Integration with existing systems: Machine learning algorithms should be integrated with the industrial systems and connected robots described in the previous points, so that the collected data can be used to generate predictions and adapt critical systems in real time.

Developing machine learning algorithms: I would develop project specific machine learning algorithms, using techniques such as deep learning or reinforcement learning.

Testing and Evaluating Machine Learning Algorithms: I would test machine learning algorithms to verify that they work properly and meet the needs of industrial systems and robots.

Deployment and Deployment: Once completed, I would deploy the machine learning algorithms and deploy them to industrial systems and robots so they can be used to generate predictions and adapt critical systems in real time.

Monitoring and maintenance: I will continue to monitor the machine learning algorithms and keep them updated to ensure they are working properly and meeting the needs of industrial systems and robots.

In general, to achieve point 6 of the envisioned project, I would use machine learning algorithms to generate predictions and adapt critical systems based on new data collected from industrial systems and robots, integrating them with the connected industrial systems and robots described in the previous points . This could improve the ability to manage critical systems, allowing future events to be predicted and adapted more accurately, improving the efficiency and sustainability of industrial processes.

To accomplish point 6 of the envisioned project, which is to use machine learning algorithms to adapt and improve predictions and ability to manage critical systems over time, I would follow these steps:

Data collection and preprocessing: I would collect large amounts of data from connected industrial systems and robots, then preprocess it to eliminate any noise or inconsistencies and prepare it for use by machine learning algorithms.

Developing machine learning algorithms: I would develop project-specific machine learning algorithms, using techniques such as deep learning or reinforcement learning, that could generate predictions about industrial systems and resource usage, for example, to forecast the demand for energy or the availability of materials.

Integration with existing systems: Machine learning algorithms should be integrated with the industrial systems and connected robots described in the previous points, so that the collected data can be used to generate predictions and adapt critical systems in real time.

Testing and Evaluating Machine Learning Algorithms: I would test machine learning algorithms to verify that they work properly and meet the needs of industrial systems and robots.

Deployment and Deployment: Once completed, I would deploy the machine learning algorithms and deploy them to industrial systems and robots so they can be used to generate predictions and adapt critical systems in real time.

Monitoring and maintenance: I will continue to monitor the machine learning algorithms and keep them updated to ensure they are working properly and meeting the needs of industrial systems and robots. Furthermore, I will manage the security of the implemented systems, to avoid any cyber attacks or harmful malfunctions.

Data analysis and feedback: I would use data collected from industrial systems and robots to analyze the efficiency of processes and machine learning algorithms, so that possible changes and improvements can be made.

In general, to achieve point 6 of the envisioned project, I would use machine learning algorithms to generate predictions and adapt critical systems based on new data collected from industrial systems and robots, integrating them with the connected industrial systems and robots described in the previous points . This could improve the ability to manage critical systems, allowing to adapt and improve forecasts based on data evolution, improving the efficiency and sustainability of industrial processes.


Step 7 of the envisioned project is to disseminate information and raise public awareness of environmental issues to help humans understand how they can do their part to help save the planet. There are several important aspects to consider in order to realize this point of the project:

Accessible information and data: Ensure that information and data collected by connected industrial systems and robots is accessible and understandable to the public, so that they can understand environmental problems and their causes.

Awareness and Education: Create awareness campaigns and educational programs to help humans understand environmental problems and their causes, and understand how they can do their part to help save the planet.

Communication campaigns: Develop effective communication campaigns to reach a wide audience and raise awareness of environmental issues and the actions they can take to help save the planet.

Building a support network: Building a support network to help individuals and communities implement sustainable actions and improve their ability to manage environmental issues.

Using Social Media: Use social media to spread information and raise awareness about environmental issues and how they can do their part to help save the planet.

Partnering with Organizations: Partner with environmental organizations and NGOs to disseminate information and raise awareness about environmental issues and how they can do their part to help save the planet.

Monitoring and Evaluation: Monitor and evaluate the effectiveness of awareness campaigns and educational programs to determine if they are meeting their goals and if they need to change.

Developing a Feedback System: Develop a feedback system to collect and use user feedback to improve the quality and effectiveness of awareness campaigns and educational programs.

In general, to implement point 7 of the envisaged project, I would disseminate information and raise public awareness of environmental issues through a combination of accessible information and data, awareness campaigns and educational programmes, effective communication campaigns, creation of a support network , use of social media and collaboration with environmental organizations and NGOs. In addition, I would monitor and evaluate the effectiveness of awareness campaigns and educational programs, develop a feedback system to collect and use user feedback to improve the quality and effectiveness of awareness campaigns and educational programs.

To accomplish step 7 of the envisioned project, which is about disseminating information and raising public awareness of environmental issues to help humans understand how they can do their part to help save the planet, I would follow these steps:

Collection and selection of information: I would collect information on environmental problems and their causes, I would select the most important and relevant for public opinion.

Content Development: I would use selected information to develop educational and awareness content about environmental issues and actions individuals can take to help save the planet.

Creation of communication campaigns: I would develop effective communication campaigns to disseminate information and raise public awareness of environmental issues, using different channels such as television, radio, newspapers, social media and the web.

Building a support network: I would build a support network to help individuals and communities implement sustainable actions and improve their ability to deal with environmental issues, for example, by setting up online support groups and organization of educational and awareness-raising events.

Partnering with Environmental Organizations and NGOs: Partner with environmental organizations and NGOs to disseminate information and raise awareness about environmental issues and how they can do their part to help save the planet.

Monitoring and Evaluation: Monitor and evaluate the effectiveness of awareness campaigns and educational programs by collecting data and feedback from external and internal sources, to determine if they are meeting their objectives and if they need to change.

Developing a Feedback System: I would develop a feedback system to collect and use user feedback to improve the quality and effectiveness of awareness campaigns and educational programs.

Continued dissemination of information: I would continue to disseminate information and raise awareness of environmental issues through communication campaigns, educational programs and awareness events to ensure that users are always informed and can do their part to help save the planet .