Road anomalies and irregularities such as potholes and uneven surfaces are a common hazard in South East Asia and developing countries. Such hazards pose a threat to the safety and well-being of both civilians going about their daily routine and tourists who are exploring the city. Since bicycles and rickshaws are still a common mode of transport used by both civilians and tourists in many South East Asian countries, it is essential to improve the overall quality and smoothness of pavements which are traversed by these vehicles. Management of international sporting and recreational events also require satisfactory road and pavement conditions. Before pavement conditions can be improved, it is an essential prerequisite to obtain comprehensive information about road irregularities such as the location and also severity of the road irregularity (depth of the potholes and height of bumps). In this paper, we propose a method for obtaining mathematical models that represent the overall condition of the pavements that are part of a commonly traversed cycling route. Such mathematical models and coefficients can be stored in the cloud of an Internet of Things (IOT) data analytics systems subsequently leading to identification of regions with severe road irregularities. ABSTRAK:  Kerosakan pada permukaan jalan raya merupakan salah satu faktor risiko kemalangan yang berlaku secara meluas di negara Asia Tenggara dan negara membangun yang lain. Memandangkan kenderaan seperti beca dan basikal masih diguna pakai secara meluas di negara membangun, adalah mustahak untuk membaik pulih kerosakan jalan raya. Pengurusan sukan antarabangsa dan rekreasi juga memerlukan keadaan jalan dan laluan pejalan kaki yang baik. Sebelum kerja membaik pulih dapat dilakukan, maklumat lengkap mengenai tahap kerosakan jalan raya dan lokasi kerosakan diperlukan. Dalam kajian ini satu kaedah telah diperkenalkan untuk mendapatkan persamaan matematik yang menggambarkan keadaan sebenar permukaan jalan raya, di mana sebahagiannya merupakan laluan berbasikal yang selalu digunakan. Model matematik dan pekali ini boleh di simpan dalam sistem analisis data awan Internet Benda (IOT) kemudiannya dapat mengenal pasti kawasan jalan yang rosak dan tidak rata.