A policewoman, Mrs Ikwen Onne Orvononne, who was awarded PhD in computer science at the University of Calabar (UNICAL) last Saturday has recommended the use of artificial intelligence (AI) by the Nigeria Police Force (NPF) to detect and prevent crime.
Orvononne made the recommendation when she analysed her thesis topic titled: “Enhancing Crime Prediction Using Machine Learning” know as “Algorithm” at a ceremony held in Calabar.
In the thesis, she recommended the use of artificial intelligence in the crime detection and crime prevention rather than relying heavily on paper work and manual cabinets.
It is claimed that she is the first policewoman of Cross River origin to bag a PhD in computer science from UNICAL since the inception of computer science department in 1979.
The police officer said the use of artificial intelligence has become necessary given the manpower shortage in the force owing to retirement and death.
“United Nations standard for the police to population is one police officer for every four hundred and fifty citizens.
“With the ever-growing population, estimated at 226 million Nigerians by the Nigeria Population Commission (NPC), and about 371,800 police officers, according to the Nigeria Police Force, the present police to population ratio in Nigeria is one police officer to 607 citizens. With a difference of about 157 additional citizen-load to a Nigeria policeman.
“International policing standard shows that Nigeria is grossly under-policed leading to a defect in effective and efficient policing,” she said.
Orvononne stated that traditional methods for crime prediction often rely on statistical models or expert knowledge, which may not capture complex patterns and dynamics inherent in crime data.
She said that to address these limitations associated with manpower shortage, Orvononne averred that the study makes use of advanced machine learning techniques to in the analyses of large and diverse datasets to provide accurate and timely predictions.
Orvononne identified Akpabuyo and Abi local government Areas as two LGAs with high prevalence of stealing in Cross River State.
“Based on findings, my thesis revealed stealing is prevalent in Akpabuyo and Abi LGA in Cross River State.
“We already know that there is a problem and that is why we are trying to proffer solutions,” she said.
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