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    Development of a GSM based Vehicle Demobilizer and Tracking System
    (ABUAD Journal of Engineering Research and Development (AJERD), 2023) Jimada-Ojuolape, Bilkisu; Spencer, Oluwafunto; Balogun, Monsurat
    Vehicle hijacking remains a pervasive global issue, posing heightened risks, especially when owners face armed hijackers. Concurrently, the disposal of old mobile phones contributes significantly to the escalating electronic waste (e-waste) challenge, emphasizing the imperative of responsible recycling practices. Addressing these concerns, this paper introduces a GSM-based vehicle demobilizer and tracking system, utilizing a cost-effective mobile phone connected to the device through a SIM card and operating with an NE 555 timer IC in bistable mode. In the event of a hijacking, a call to the mobile phone triggers the device, halting the vehicle. In the prototype design presented in this paper, the result of the output is represented by an LED to show that the circuitry actually works. When the device was tested, the LED illuminated when a call was placed to the mobile phone connected to the device which signifies that the circuit works and can achieve its purpose. The resulting design also shows that the vehicle owner can prevent his car from being stolen away even after it has been hijacked without self-endangerment and within a short time frame.
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    Conceptual Design and Turbine Selection for a Micro Hydropower System Using Multi-Criteria Analysis
    (Nigerian Journal of Engineering, 2023) Jimada-Ojuolape, Bilkisu; Balogun, Monsurat; Adesina, Lambe
    Nigeria has grappled with a persistent electricity supply challenge characterized by surging demand, inadequate maintenance of power generation infrastructure, and a host of other issues. This ongoing predicament has given rise to frequent power outages, compelling citizens to resort to expensive alternatives like petrol and diesel generators. Moreover, a substantial number of Nigerian households rely on motorised boreholes for their water supply. Considering these circumstances, this study proposes an innovative solution in the form of a micro hydropower system that harnesses the existing tank-borehole setups within homes to generate electricity. The primary objective of this research is to define the specifications of the central subsystem, namely the turbine, by employing the multi-criteria analysis method, thereby facilitating the practical implementation of the proposed energy generation scheme. In particular, this study delves into an evaluation of two turbine options: Pelton and crossflow turbines. The results of the analysis revealed that the crossflow turbine emerges as the most suitable choice for this application, leading to the exclusion of other turbine alternatives such as the Francis and Turgo turbines.
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    Using Artificial Intelligence to Predict Animal Behaviour in Food Webs
    (Transactions on Machine Learning and Artificial Intelligence, 2017) Aduragba, Tahir; Ahmed, Abdulkadir; Jimada-Ojuolape, Bilkisu; Ajani, Ayodeji; Adedoyin, Yinka
    Overfishing of species in the marine life has caused oceans to become deserts at a fast pace. The population of specific species such as Cod and Haddock has reduced over the years. This has affected countries that hugely depend on them as a source of food. This study used Dynamic Bayesian Network (DBN) to predict animal behaviour in a food web. Two independent biomass surveys from the North Sea were used to learn predictive models and test them on the Northern Gulf Ocean. The resulting predictive model is expected to unveil useful information about what affects the population of fishes in the Northern Gulf Ocean. In addition, the predictive model was used to make predictions into the future about the effects of tampering with the population of specific species of fish in the same region. The focus was on the Cod species in the George’s Bank in relationship to species network in their food web. Looking at their biomass states and the effects it has on the hidden dependence when there is a change in their biomass states. Also, the different predictive models were used to evaluate species in the George’s Bank based on their performance. The result from the experiment shows that there is a hidden dependence, which is responsible for the collapse of species (Cod); due to the temperature or salinity of the ocean.