Neighbourhood theft persists in peri-urban and urban Tanzania despite widespread community-led guarding. While commercial guard-tour systems exist, they do not fit neighbourhood committee realities of member contributions, local oversight, and police liaison. This study proposes a holistic, committee-centric monitoring and management framework by translating qualitative field evidence into algorithmic modules. Using a hybrid inductive–deductive thematic approach, this study conducted semi-structured interviews and focus group discussions with private night guards (including Maasai youth), community leaders, members and non-members, and police in Goba Ward, Dar es Salaam. Transcripts were coded in MAXQDA (open → axial → selective), yielding nine themes: last-mile shift gap, patrol vs. idling, sanctions without evidence, financial fragility, transparency demand, communication latency, equipment/device readiness, police evidence need, and community diffusion gap. Each theme was mapped to a system algorithm (A1–A9), including shift-completion verification, patrol-path and idle detection, attendance-to-payroll linkage, contribution and arrears management, dashboards, multi-channel communication, equipment health tracking, standardized incident handover, and a start-a-zone wizard. The resulting architecture aligns software functions with local governance logic, strengthening accountability, transparency, and collaboration with police. The framework offers a practical pathway to sustain community-led security and can be extended to Internet of Things (IoT)/predictive analytics in future deployments.
Mahuwi et al. (2026) studied this question.