AI for Sustainability: A Blueprint for a Greener Nigeria

As the world grapples with climate change, environmental degradation, social inequality, food inflation, and the high cost of living, Nigeria, like many other countries, is seeking innovative solutions to ensure a sustainable future. Artificial Intelligence (AI) has emerged as a powerful transformative tool in this regard, offering unprecedented opportunities to drive sustainable development. AI has the potential to revolutionise various sectors as its applications extend beyond automation and data analysis. It offers innovative solutions to pressing global challenges, including sustainability. In Nigeria, a country rich in natural resources but facing significant environmental and socio-economic pressures, AI can play a crucial role in driving sustainable development.    This article explores how AI can drive sustainable solutions in Nigeria, examining real-world AI success stories, identifying and scaling AI-driven solutions, and unlocking AI’s potential in shaping the future of sustainability, efficient management of resources, and reducing waste. It also tackles environmental issues, such as environmental degradation, energy shortages, and waste management and infrastructure.

Real-World AI Success Stories in Sustainability

1. Agriculture and Precision Farming:

Agriculture is a critical sector in Nigeria, employing over 70% of the rural population. However, the industry faces challenges of poor crop yields, unpredictable weather patterns, and pest infestations. AI-powered precision farming solutions offer a way to enhance productivity while reducing environmental impact. For instance, AI algorithms can analyse satellite imagery and weather data to predict crop yields, monitor soil health, and optimise irrigation.  Precision agriculture has been used in various locations in Nigeria, and the result has been massive.  AI-powered drones and satellite imagery have been used to monitor crop health, optimise irrigation, and reduce pesticide usage. This has increased crop yields by up to 20% while minimising environmental impact.

 A very notable case study of AI's success stories in Agriculture and precision farming is  Plantix.  Plantix is an AI-powered mobile application used in India to help farmers identify plant diseases and deficiencies through image recognition. The app has been used by millions of farmers in India, with over 30 million images analysed to date. The AI-based tool has been able to accurately identify crop diseases with up to 95% accuracy, leading to better pest management and higher crop yields.

Impact: In regions where Plantix is used, crop loss due to diseases has decreased by 20–30%, improving food security for local farmers in India.

2. Energy Management:

Nigeria faces frequent power outages and collapses of the national grid and a reliance on fossil fuels for electricity. AI can optimise energy consumption and integrate renewable energy sources, such as solar and wind, into the national grid. In countries like Kenya, AI is used to predict electricity demand and optimise energy distribution, reducing blackouts and enhancing grid reliability. Nigeria can adopt similar AI technologies to analyse energy usage patterns, automate load balancing, and forecast power demand, thus making the energy sector more efficient and sustainable.

 Kenya’s successful AI integration to optimise energy distribution and manage electricity supply in the country shows that AI can also improve power supply in Nigeria. AI implementation has resulted in a 20% reduction in blackouts, with significant cost savings on energy production and maintenance. The AI solution also helped the grid accommodate more renewable energy sources, increasing Kenya's renewable energy contribution to over 80% of its total energy mix. 

3. Waste Management and Recycling:

Effective waste management remains a major challenge in Nigeria, generating over 32 million tonnes of solid waste each year. This waste includes about 2.5 million metric tonnes of plastic, placing Nigeria among the top global contributors to oceanic plastic pollution and worsening the climate.  Projections indicate that the total waste output could reach 107 million metric tonnes by 2050 if current trends persist. However, the waste collection and disposal infrastructure is inadequate, with a large proportion of waste remaining uncollected or improperly managed. It's reported that a considerable percentage of waste is handled through informal sectors, like scavenging and informal recycling, which recover around 80% of recyclable waste in cities like Lagos. There is a national effort to address this issue through policies promoting waste recycling and private-sector investment. However, the sector is still largely informal, and formal recycling initiatives remain limited.

AI can help optimise waste collection routes, predict waste generation trends, and enhance recycling processes. For example, AI-powered sorting machines can differentiate between various waste materials, enabling more efficient recycling. Such systems are already in use in countries like Japan, where AI sorts recyclables with greater accuracy, significantly reducing landfill waste.

Also in Finland, AI-powered robots are used in waste management.  ZenRobotics in Finland has deployed AI-powered robots to sort waste materials in recycling plants. These robots can identify waste types using AI algorithms and sort them accordingly.

The outcome for ZenRobotics is massive. The AI-powered robots have increased sorting efficiency by 50% and significantly reduced labour costs in recycling facilities. They can sort waste at a rate of up to 4,000 picks per hour, which is much faster than manual sorting. Implementing in waste sorting has led to a 20% increase in the amount of recyclable materials being processed, reducing landfill waste and boosting recycling rates.

4. Climate Change Monitoring:

Climate change poses a significant threat to Nigeria, manifesting in severe droughts, floods, and rising temperatures. AI-driven climate models can predict weather patterns and assess the impact of climate events, enabling proactive planning and disaster management. Companies like Google have developed AI systems that can accurately forecast floods, giving communities enough time to prepare and mitigate damage. Implementing similar AI-based climate monitoring tools in Nigeria can help anticipate extreme weather conditions, protect vulnerable communities, and develop resilience strategies.

Google Flood Forecasting Initiative in India and Bangladesh

Google's AI-powered flood forecasting initiative provides early flood warnings to communities in India and Bangladesh. The system uses AI models that analyse weather data, river levels, and terrain information to predict when and where floods will occur.

Since its launch, the AI system has sent over 115 million notifications to people in affected areas, covering more than 40 million people. The AI predictions are up to 75% accurate in predicting floods several days in advance.

This early warning system has helped reduce casualties and property damage in flood-prone regions. It has also allowed local authorities to plan and execute timely evacuation procedures, significantly minimising the impact of floods on communities.

Recommended for you:

AI in Warfare: Exploring Key Benefits and Critical Risks

5. Anti-Corruption and Good Governance:

Artificial Intelligence (AI) has proven to be a powerful tool in fighting corruption and improving governance.  While the success stories of AI implementation from different regions illustrate the potential of AI-driven solutions, the same can be replicated in Nigeria, where corruption is a significant issue. Here are some notable AI use cases and success stories in this area:

 i. Fraud Detection and Prevention in Public Finance

Use Case: AI algorithms can analyse financial data from government transactions to detect anomalies and suspicious activities, which might indicate corruption or fraud. Machine learning models can identify patterns that suggest the misuse of funds, procurement fraud, or financial mismanagement.

Success Story: In Kenya, AI-powered platforms have been employed to monitor government expenditures, especially in high-risk sectors like health and education. Such systems helped detect fraudulent claims and saved millions of dollars. While Nigeria has yet to widely adopt similar tools across all states, there have been pilot programs where AI was used to identify ghost workers on government payrolls, leading to savings of billions of Naira.

ii. Automating Anti-Corruption Monitoring:

Use Case: AI can automate the monitoring of government activities by scanning documents, emails, and public records for red flags, such as conflict of interest, bribery, and nepotism. This reduces the manual effort required in auditing and speeds up the detection process.

Success Story: Brazil's anti-corruption agency has used AI tools to analyse thousands of procurement contracts. The AI system flagged contracts with a higher likelihood of corruption, leading to investigations and prosecutions. Similarly, the Economic and Financial Crimes Commission (EFCC) in Nigeria could leverage AI to improve its data analytics capabilities and increase the efficiency of corruption investigations.

iii. E-Government Systems for Transparency:

Use Case: Implementing AI-driven e-governance platforms from budgeting to public procurement can make government processes more transparent. AI chatbots can also help citizens report corruption anonymously and safely.

Success Story: Estonia is a global leader in e-governance, using AI to streamline government services and increase transparency. Citizens can access most public services online, and AI helps to ensure that all transactions are traceable. In Nigeria, the introduction of online procurement portals in some states, though not fully AI-driven, has helped reduce the chances of manipulation in contract awards.

iv. Data Analytics for Law Enforcement

Use Case: AI can be utilised by anti-corruption agencies to analyse large datasets from different sources (such as bank records, asset declarations, and travel histories) to identify links between corrupt activities and individuals or organisations.

Success Story: In the United States, AI-based data analysis tools have been used by the IRS to uncover complex financial crimes involving money laundering and tax evasion. Nigeria's anti-corruption agencies could enhance their capabilities by adopting similar technologies to track illicit financial flows and recover stolen assets.

While these examples showcase the potential of AI in governance and anti-corruption, significant challenges remain in Nigeria, including data availability, infrastructural limitations, and the need for legal frameworks to support AI deployment. However, with targeted investments and political will, AI can become a crucial part of the solution to combating corruption in the country.

 6. Enhancing Electoral Integrity:

The Independent National Electoral Commission (INEC) can utilise AI in several ways to make elections more transparent, credible, and less prone to manipulation:

• Automated Voter Verification: AI-based facial recognition and biometric analysis can ensure that only eligible voters cast their votes, reducing double voting and impersonation incidents. Biometric verification, such as fingerprints and facial recognition, can help confirm the identity of voters during registration and on election day, thus reducing fraud.
• Election Monitoring with AI-Powered Tools: AI algorithms can analyse social media and online platforms to detect misinformation and disinformation campaigns aimed at influencing voter behaviour. AI-powered tools can monitor for electoral malpractices, such as vote buying or intimidation, by analysing video footage, social media chatter, or election-related data.
• Data Analysis for Results Verification: AI can be used to compare election results from various polling stations to detect anomalies or discrepancies. Machine learning algorithms can identify patterns that indicate irregularities or attempts to manipulate the vote count.
• Blockchain-Based Voting: Although still a developing concept, AI can work alongside blockchain technology to ensure a transparent and tamper-proof digital voting process. Each vote is securely recorded and can be audited, reducing opportunities for vote tampering.

Brazil's Use of AI in Election Monitoring

Brazil has a history of concerns over election security and voter fraud. In recent years, the country has implemented AI to help monitor the electoral process, particularly during its presidential elections.

Success Story: During the 2018 elections, Brazil's electoral authorities used AI to analyse social media data for signs of disinformation and fake news that could influence voters. The AI system was able to detect bots and automated accounts spreading false information, which helped the authorities take timely action to counter disinformation campaigns. Additionally, AI-driven systems were used to monitor voting patterns and flag suspicious activities in real-time, enhancing the transparency of the election process.

India's Use of AI for Voter Fraud Detection

India, being the world's largest democracy, faces significant challenges in managing elections across its vast and diverse population. One of the persistent issues has been voter impersonation and multiple registrations.

Success Story: AI has been used in some states to detect duplicate voter registrations by analysing biometric data, such as facial recognition and fingerprints. This helped eliminate millions of fake or duplicate entries from the electoral roll.  In addition, AI was used to detect anomalies in voting patterns that could indicate electoral malpractice, such as vote buying or coercion. These efforts contributed to more credible elections in regions where the technology was deployed.

United States: AI in Election Security:

The U.S. has faced growing concerns over cybersecurity and foreign interference in elections. In response, various AI-driven solutions have been employed to safeguard the integrity of the election process.

Success Story: In the 2020 presidential election, AI was used to monitor online misinformation and foreign disinformation campaigns. Platforms like Facebook and Twitter deployed AI algorithms to detect and remove false content that could mislead voters. Moreover, AI-powered tools were used to analyse voter registration databases and detect attempts to hack or tamper with voter information, thereby improving the security of the election infrastructure.

Sierra Leone’s Blockchain and AI-Powered Voting System:

Sierra Leone made history in 2018 by becoming the first country to use blockchain technology in a presidential election. While blockchain ensured transparency, AI played a role in analysing the data for any irregularities.

Success Story: AI algorithms helped ensure that the votes recorded on the blockchain matched the tallied results, providing an additional layer of verification. This innovative approach showed that combining AI with emerging technologies like blockchain could improve election transparency and trust in regions prone to electoral fraud.

Key Takeaways

These examples highlight how AI can be applied in different aspects of the electoral process, such as:

•  Detecting and mitigating disinformation.
• Preventing voter fraud through biometric verification.
• Ensuring cybersecurity in election systems.
• Monitoring election results for anomalies.

By incorporating AI, election bodies can achieve greater transparency, reduce the potential for manipulation, and enhance public confidence in the electoral process. We are calling on INEC to adopt AI to make the 2027 general election more transparent.

Identifying and Scaling AI-Driven Solutions

Scaling AI-driven solutions in Nigeria requires a multifaceted approach, including fostering innovation, building partnerships, and improving infrastructure.

1. Building a Robust Digital Infrastructure:

To successfully deploy AI-driven solutions, Nigeria needs to invest in digital infrastructure, such as data centres, high-speed internet, and cloud computing capabilities. Enhanced connectivity and access to data will enable the collection and analysis of real-time information, essential for effective AI deployment. The government can collaborate with private sectors to develop the necessary infrastructure, making AI technology accessible to various sectors.

2. Developing Local AI Talent:

Training and upskilling the workforce is vital for the successful adoption of AI in sustainability initiatives. Establishing AI research hubs and promoting STEM education (science, technology, engineering, and mathematics) can help build local expertise in AI technologies. For example, programs like Data Science Nigeria are already working towards equipping young Nigerians with AI and data science skills, creating a skilled workforce capable of driving AI innovations in sustainability.

3. Encouraging Public-Private Partnerships:

Collaborative efforts between the government, academia, and private sector can accelerate the adoption of AI-driven sustainability solutions. Companies can partner with research institutions to develop AI applications tailored to local needs, while government policies can incentivise sustainable practices and provide regulatory support for AI initiatives. Public-private partnerships can also facilitate the deployment of AI solutions in sectors like agriculture, waste management, and energy.

4. Ensuring Data Availability and Quality:

Data is crucial for AI development, yet access to high-quality data remains a challenge in Nigeria. Establishing data-sharing frameworks, creating open data repositories, and improving data governance policies can help overcome this challenge. AI models rely on vast amounts of data to function effectively, and having accurate, diverse, and reliable datasets will enhance the accuracy of AI-driven sustainability solutions.

Unlocking AI’s Potential in Shaping the Future of Sustainability

AI has the potential to revolutionize the sustainability landscape in Nigeria by providing data-driven insights, automating processes, and enhancing decision-making. Here's how AI can shape a sustainable future:

 1. Accelerating Renewable Energy Adoption:

AI can support the transition to renewable energy by optimising solar panel placement, predicting energy production, and managing energy storage systems. AI algorithms can analyse geographic and meteorological data to identify optimal locations for solar farms, increasing energy generation efficiency. Moreover, AI can help integrate renewable energy into the national grid by predicting fluctuations in supply and demand, enabling better management of energy resources.

2. Enhancing Smart City Development:

Smart cities leverage AI to improve urban living by optimising transportation, reducing energy consumption, and managing resources efficiently. For example, AI can be used to monitor air quality, regulate traffic flow, and detect water leakages in real-time. In Nigeria, adopting AI-driven smart city solutions can alleviate challenges like traffic congestion, pollution, and waste management, creating more liveable and sustainable urban environments.

3. Improving Natural Resource Management:

AI can be pivotal in managing natural resources like water, forests, and fisheries. For instance, AI-powered drones can monitor deforestation activities, track illegal fishing, and detect water pollution. In countries like Brazil, AI is used to monitor the Amazon rainforest, helping authorities combat illegal logging. Nigeria can leverage similar technologies to safeguard its natural resources, promote sustainable practices, and mitigate the adverse effects of resource depletion.

 4. Driving Sustainable Business Practices:

AI can help businesses optimise their operations to minimise environmental impact. Companies can use AI to analyse supply chains, reduce waste, and lower carbon footprints. For instance, AI-powered platforms can recommend sustainable sourcing practices or identify inefficiencies in production processes. By integrating AI into their sustainability strategies, Nigerian businesses can achieve both economic and environmental benefits.

Recommended for you:

PH Green City: Leading Sustainable Urban Development

Conclusion

Artificial Intelligence holds the potential to transform Nigeria's sustainability landscape by offering innovative solutions to pressing environmental and resource management challenges. With the right investments in digital infrastructure, local talent development, and data governance, AI can unlock unprecedented opportunities for sustainable development in Nigeria. Real-world success stories in agriculture, energy management, waste management, and climate monitoring demonstrate AI's capability to drive impactful change. By identifying, scaling, and integrating AI-driven solutions across various sectors, Nigeria can shape a sustainable future where technology and the environment coexist harmoniously.

 Leveraging AI for sustainability will not only address immediate challenges but also pave the way for long-term economic and environmental prosperity. As Nigeria continues to embrace AI, the country stands to gain from reduced resource wastage, enhanced disaster management, and a more resilient economy poised for sustainable growth.

 FAQs

How AI Can Be Used In Fighting Corruption In NNPC

The NNPC has been at the centre of numerous corruption scandals over the years. AI can help curb corruption within the corporation by: Automating Audits and Compliance Checks: AI systems can monitor and analyse financial transactions, procurement processes, and contracts to detect irregularities or red flags indicative of corruption, such as inflated contract values or unapproved payments. Machine learning algorithms can be trained to identify common patterns associated with fraud in financial records. Predictive Analytics for Oil Theft and Diversion: AI can analyse data from pipelines, production facilities, and distribution networks to detect abnormal patterns that may indicate oil theft, sabotage, or diversion of petroleum products. AI-based predictive maintenance can also help prevent illegal tapping into pipelines by identifying vulnerabilities. Tracking Payments and Revenues: AI-powered analytics tools can be used to track revenue streams and payments within the NNPC and its subsidiaries. By monitoring the flow of funds, AI can help detect discrepancies between reported production and sales figures, reducing the likelihood of corruption.

How AI Can Address Corruption in NDDC

The Niger Delta Development Commission (NDDC) has faced allegations of misappropriation of funds and contract-related corruption. AI can help combat these issues through: AI-Driven Contract Monitoring: AI can analyse contract awards, project costs, and completion timelines to identify suspicious patterns. For instance, if certain contractors consistently win bids despite higher costs or if projects are habitually delayed without penalties, the system can flag these for further investigation. Geospatial Data Analysis for Project Verification: Using AI in conjunction with satellite imagery or drone data, the government can monitor the progress of infrastructure projects funded by the NDDC. AI algorithms can compare the actual progress of projects with reported milestones to detect discrepancies, ensuring that funds are not misappropriated. Sentiment Analysis for Public Feedback: AI can analyse public complaints and feedback about NDDC projects on social media, news reports, and online forums. This analysis can help identify cases of non-performance or fraudulent projects by detecting trends in citizen dissatisfaction.

What are the Challenges and the Way Forward for AI in Nigeria?

While AI holds great potential for improving governance, its implementation in Nigeria would require significant investments in infrastructure, capacity building, and regulatory frameworks to ensure data privacy and security. Collaboration between government agencies, tech companies, and civil society would also be essential to effectively deploy AI solutions in these areas. AI can be a game-changer for Nigeria in tackling issues related to elections, governance, and corruption. However, for these solutions to be effective, there must be a commitment from both the government and society to embrace transparency, data sharing, and ethical practices in deploying AI technologies.