Innovation: The innovations are 1. Dynamic pricing: AI can be used to develop a dynamic pricing system that adjusts rental prices based on supply and demand. This system can analyze various factors such as location, availability, and user demand to suggest optimal pricing for the rental property or resource. 2. Fraud detection and prevention: AI can be used to identify fraudulent activities and prevent them from occurring. By analyzing user behavior and transactions, AI can identify suspicious activities such as fake listings or payment fraud and alert users or take action to prevent them. 3. Personalized user experience: AI can be used to create a personalized user experience for each individual user. By analyzing user data and behavior, AI can suggest personalized recommendations, create customized profiles, and provide personalized support and communication. 4.Predictive maintenance: AI can be used to predict maintenance issues and prevent downtime for rental properties or resources. By analyzing usage patterns and data, AI can identify potential maintenance issues and suggest preventive maintenance measures to minimize downtime. For satellite imaging system 1. Obtaining clarity through Non-Zero Matrix Factorization could be achieved. 2. Cost sharing could lead to better farm ouput 3. Technology could be dispersed using Application Programming Interface on many farm and agriculture related mobile applications.

Sector/Industry Application: Agriculture

Description: The research is to help solve some basic problems in the use of rental and satellite assisted agriculture for rural farmers. Increasingcapital cost of input and demand for agricultural products implies affordable alternatives are needed. Though rental system could be aggregated using mobile application, website and instant messaging, use of satellite to optimize is yet to be fully achieved due to some problems. These problems are : 1.Limited resolution: The resolution of satellite imagery is limited, which can make it difficult to identify smaller details in crops, such as individual plants or the presence of pests or diseases. 2.Cloud cover: Cloud cover can interfere with satellite imagery, making it difficult to obtain accurate and timely data. 3.Cost: The cost of satellite imagery can be prohibitive for smaller farmers or those in developing countries. 4.Technical knowledge: Satellite imagery-driven agriculture requires technical knowledge to use effectively, which can be a barrier for some farmers. 5.Interpretation: The interpretation of satellite imagery can be complex and require specialized expertise. 6.Data accuracy: The accuracy of satellite imagery can be affected by a range of factors, such as atmospheric conditions and sensor calibration.

Problem: Problem of increasing input cost and down time in sourcing for farm machineries could be solved through robost rental system. Satellite assisted agriculture could be of benefit in the following ways. 1.Crop Monitoring: Satellite imagery can provide high-resolution images of crops, allowing farmers to monitor crop health, growth patterns, and identify areas of stress. This data can be used to optimize irrigation, fertilizer, and pesticide use. 2.Yield Estimation: Using satellite imagery, farmers can estimate crop yields by analyzing plant density, growth patterns, and other factors. This information can be used to make informed decisions about harvesting, marketing, and pricing. 3.Soil Analysis: Satellite imagery can be used to identify soil types and analyze soil moisture levels, allowing farmers to optimize soil management practices and improve crop yield. 4.Climate Analysis: Satellite imagery can be used to monitor weather patterns, predict weather events, and plan crop management practices accordingly. 5.Land Management: Satellite imagery can be used to monitor land use patterns, identify areas of erosion, and monitor conservation efforts. Small holder farmers would be able to share cost and get excellent technology backup services in through the research.