Here is a detailed solution motivated by @Arthur's. Let $\mathbf w \in \mathbb R^n$, non of whose coordinates is $0$. For any real $z$, define
$$G_{\mathbf w,z} := \{\mathbf x \in \mathbb R^n | \mathbf w^T \mathbf x \le z\}, \;H_{\mathbf w,z} := \{\mathbf x \in \mathbb R^n | \mathbf w^T \mathbf x = z\}.$$
The sought-for integral is precisely
$$\int_{[0,1]^n} f(\mathbf w^T\mathbf x)d\mathbf x= \mathbb E_{x_1,\ldots, x_n \sim \mathcal U[0, 1]} [f(\mathbf w^T \mathbf x)]$$
with the choice $w_1 = \ldots w_n = 1$.
Now, let $F_{\mathbf w}$ be the cdf of $\mathbf w^T\mathbf x$ for i.i.d $x_1,\ldots,x_n \sim \mathcal U[0,1]$. Then its not hard to see that
$F_{\mathbf w}(z) = \operatorname{vol}_n (G_{\mathbf w,z} \cap[0,1]^n)$,
with density $f_{\mathbf w}(z) = \|\mathbf w\|_2^{-1} \operatorname{vol}_{n-1} (H_{\mathbf w,z} \cap[0,1]^n)$. By elementary properties of expectations, one has
$$
\begin{split}
\int_{[0,1]^n} f(\mathbf w^T\mathbf x)d\mathbf x &= \mathbb E_{x_1,\ldots, x_n \sim \mathcal U[0, 1]}f(\mathbf w^T\mathbf x) = \int_{-\infty}^\infty \mathbb E(f(\mathbf w^T\mathbf x) | \mathbf w^T\mathbf x = z)f_{\mathbf w}(z)dz\\
&= \int_{-(-\mathbf w)_+^T\mathbf 1_n}^{(\mathbf w)_+^T\mathbf 1_n} \|\mathbf w\|_2^{-1}\operatorname{vol}_{n-1} (H_{\mathbf w,z} \cap[0,1]^n)f(z)dz.
\end{split}
$$
Invoking Theorem 4 of this paper yields
$$
\|\mathbf w\|_2^{-1}\operatorname{vol}_{n-1} (H_{\mathbf w,z} \cap[0,1]^n) = \frac{1}{(n-1)! \prod_{k=1}^n w_k}\sum_{K \subseteq [\![n]\!]}(-1)^{\#K}\left(z - \mathbf w^T\mathbf 1_K\right)_+^{n-1},
$$
where $\mathbf w^T \mathbf 1_K := \sum_{k \in K}w_k$. Putting things together gives
$$
\int_{[0,1]^n} f(\mathbf w^T\mathbf x)d\mathbf x= \frac{1}{(n-1)! \prod_{k=1}^n w_k}\sum_{K \subseteq [\![n]\!]}(-1)^{\#K}\sigma_{\mathbf w, K}(f),
$$
where $\sigma_{\mathbf w, K}(f):= \Lambda_{-(-\mathbf w)_+^T\mathbf 1_n,(\mathbf w)_+^T\mathbf 1_n,\mathbf w^T\mathbf 1_K}(f)$ and
$$\Lambda_{a,b,c}(f) := \int_{a}^b \left(z - c\right)_+^{n-1}f(z)dz.
$$
Thus the whole game is about computing the numbers $\Lambda_{a,b,c}(f)$.
Examples
- Volume of hypercube $[0,1]^n$. This is a pathologically simple example and is only here to act as a sanity check. Take $w_1 = \ldots = w_n = f = 1$, and for any $K \subseteq [\![n]\!]$ with $\#K = k$, one has
$$\sigma_{\mathbf w, K}(f) = \int_{k}^n (z-k)^{n-1} dz = \frac{1}{n}(n-k)^n.
$$
Thus
$$\int_{[0,1]^n} dx_1 \ldots dx_n =
\frac{1}{n!}\sum_{k=0}^n C^n_k(-1)^k(n-k)^n = 1
$$
- Expected value of sum of $n$ i.i.d uniform random variables.
Take $w_1 = \ldots = w_n = 1$ and $f = \operatorname{id}$. For any $K \subseteq [\![n]\!]$ with $\#K = k$, one has
$$\sigma_{\mathbf w, K}(f) =
\int_0^n(z-k)^{n-1}zdz = \frac{(n - k)^n(n^2 + k)}{n(n+1)}
$$
$$
\begin{split}
\int_{[0,1]^n}(x_1+ \ldots + x_n)dx_1 \ldots dx_n &= \frac{1}{(n+1)!}\sum_{k=0}^n (-1)^kC^n_k (n-k)^{n}(n^2 + k)\\
&= \frac{1}{(n+1)!}\frac{n}{2}(n+1)! = \frac{n}{2}
\end{split}
$$