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In our World of today, the quest to get rich at all cost without working for our money has led some of our youth into crimes such as robbery and kidnapping. As a result of this and by the sheer fact that vehicles are now very expensive to buy these days, there is a need for people to safeguard their vehicles against these hoodlums to avoid loss of their precious Assets to these rampaging criminals. Tracking is technology that is used by many companies and individuals to track a vehicle, an individual or an asset by using many ways like GPS that operates using satellites and ground-based stations or by using our approach which depends on the cellular mobile towers. Vehicle tracking system is a system that can be used in monitoring and locating a vehicle, avoid theft or recover a stolen vehicle, for monitoring of vehicle routes to ensure strict compliance to an already defined vehicle routes, monitor driver’s behavior, predict bus arrival as well as for fleet management. Internet of things has made it very possible to devices to inter communicate amongst themselves and exchange information, helping in acquiring and analyzing information faster that we used to know in the past and this has helped more especially in vehicle monitoring to ensure that vehicle owners feel safe about their investments without fearing about their loss. In this paper, we propose a vehicle monitoring system based on IOT technology, using 4G/LTE to get the get the coordinate, speed, and overall condition of the vehicle, process and send to a remote server to be analyzed and used in locating the vehicle and monitor its other configured parameters. This is realized using Raspberry pi, 4G/LTE, GPS, Accelerometer and other sensors with communicate amongst themselves to get the environmental parameters which is processed and sent to a remote server where it is analyzed and represented on a map to locate the vehicle and monitor the other set parameters. 4G/LTE provides fast internet connectivity with

Big climate change data have become a pressing issue that organizations faced with methods to analyse data generated from various data types. However, storage, processing, and analysis of data generated from climate change activities are massive, which is challenging for the current algorithms to handle. Therefore, big data analytics methods are designed for significant data that is required to enhance seasonal change monitoring and understanding, ascertain the health risk of climate change, and improve the allocation, and utilisation of natural resources. This paper provides an outlook on big data analytic methods and describes how climate change and sustainability issues can be analysed through these methods. We extensively discuss big data analytic methods, strengths, and weaknesses. The purpose of analysing big climate change using these methods, the common datasets and implementation frameworks for climate change modeling using the big data analytics approach was also discussed. This big data analytics method is well timed to solve the inherent issues of data analysis and easy realization of sustainable development goals.